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

PubMed

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

2015-11-03

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

Current trends in quantitative proteomics - an update.

PubMed

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

2017-05-01

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

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

PubMed Central

Lavallée-Adam, Mathieu

2017-01-01

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

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

PubMed

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

2015-01-01

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

A 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.

Comparative and Quantitative Global Proteomics Approaches: An Overview

PubMed Central

Deracinois, Barbara; Flahaut, Christophe; Duban-Deweer, Sophie; Karamanos, Yannis

2013-01-01

Proteomics became a key tool for the study of biological systems. The comparison between two different physiological states allows unravelling the cellular and molecular mechanisms involved in a biological process. Proteomics can confirm the presence of proteins suggested by their mRNA content and provides a direct measure of the quantity present in a cell. Global and targeted proteomics strategies can be applied. Targeted proteomics strategies limit the number of features that will be monitored and then optimise the methods to obtain the highest sensitivity and throughput for a huge amount of samples. The advantage of global proteomics strategies is that no hypothesis is required, other than a measurable difference in one or more protein species between the samples. Global proteomics methods attempt to separate quantify and identify all the proteins from a given sample. This review highlights only the different techniques of separation and quantification of proteins and peptides, in view of a comparative and quantitative global proteomics analysis. The in-gel and off-gel quantification of proteins will be discussed as well as the corresponding mass spectrometry technology. The overview is focused on the widespread techniques while keeping in mind that each approach is modular and often recovers the other. PMID:28250403

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

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

PubMed

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

2016-04-01

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

Stable isotope dimethyl labelling for quantitative proteomics and beyond

PubMed Central

Hsu, Jue-Liang; Chen, Shu-Hui

2016-01-01

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

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

PubMed

Lavallée-Adam, Mathieu; Yates, John R

2016-03-24

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

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

PubMed Central

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

2012-01-01

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

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

PubMed

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

2018-05-22

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

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

PubMed

Goeminne, Ludger J E; Gevaert, Kris; Clement, Lieven

2018-01-16

Label-free shotgun proteomics is routinely used to assess proteomes. However, extracting relevant information from the massive amounts of generated data remains difficult. This tutorial provides a strong foundation on analysis of quantitative proteomics data. We provide key statistical concepts that help researchers to design proteomics experiments and we showcase how to analyze quantitative proteomics data using our recent free and open-source R package MSqRob, which was developed to implement the peptide-level robust ridge regression method for relative protein quantification described by Goeminne et al. MSqRob can handle virtually any experimental proteomics design and outputs proteins ordered by statistical significance. Moreover, its graphical user interface and interactive diagnostic plots provide easy inspection and also detection of anomalies in the data and flaws in the data analysis, allowing deeper assessment of the validity of results and a critical review of the experimental design. Our tutorial discusses interactive preprocessing, data analysis and visualization of label-free MS-based quantitative proteomics experiments with simple and more complex designs. We provide well-documented scripts to run analyses in bash mode on GitHub, enabling the integration of MSqRob in automated pipelines on cluster environments (https://github.com/statOmics/MSqRob). The concepts outlined in this tutorial aid in designing better experiments and analyzing the resulting data more appropriately. The two case studies using the MSqRob graphical user interface will contribute to a wider adaptation of advanced peptide-based models, resulting in higher quality data analysis workflows and more reproducible results in the proteomics community. We also provide well-documented scripts for experienced users that aim at automating MSqRob on cluster environments. Copyright © 2017 Elsevier B.V. All rights reserved.

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

PubMed

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

2011-03-04

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

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

PubMed Central

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

2011-01-01

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

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

PubMed

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

2017-08-15

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

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

PubMed

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

2018-05-01

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

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.

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

PubMed Central

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

2014-01-01

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

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

PubMed

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

2011-01-01

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

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

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.

Hypothalamus proteomics from mouse models with obesity and anorexia reveals therapeutic targets of appetite regulation

PubMed Central

Manousopoulou, A; Koutmani, Y; Karaliota, S; Woelk, C H; Manolakos, E S; Karalis, K; Garbis, S D

2016-01-01

Objective: This study examined the proteomic profile of the hypothalamus in mice exposed to a high-fat diet (HFD) or with the anorexia of acute illness. This comparison could provide insight on the effects of these two opposite states of energy balance on appetite regulation. Methods: Four to six-week-old male C56BL/6J mice were fed a normal (control 1 group; n=7) or a HFD (HFD group; n=10) for 8 weeks. The control 2 (n=7) and lipopolysaccharide (LPS) groups (n=10) were fed a normal diet for 8 weeks before receiving an injection of saline and LPS, respectively. Hypothalamic regions were analysed using a quantitative proteomics method based on a combination of techniques including iTRAQ stable isotope labeling, orthogonal two-dimensional liquid chromatography hyphenated with nanospray ionization and high-resolution mass spectrometry. Key proteins were validated with quantitative PCR. Results: Quantitative proteomics of the hypothalamous regions profiled a total of 9249 protein groups (q<0.05). Of these, 7718 protein groups were profiled with a minimum of two unique peptides for each. Hierachical clustering of the differentiated proteome revealed distinct proteomic signatures for the hypothalamus under the HFD and LPS nutritional conditions. Literature research with in silico bioinformatics interpretation of the differentiated proteome identified key biological relevant proteins and implicated pathways. Furthermore, the study identified potential pharmacologic targets. In the LPS groups, the anorexigen pro-opiomelanocortin was downregulated. In mice with obesity, nuclear factor-κB, glycine receptor subunit alpha-4 (GlyR) and neuropeptide Y levels were elevated, whereas serotonin receptor 1B levels decreased. Conclusions: High-precision quantitative proteomics revealed that under acute systemic inflammation in the hypothalamus as a response to LPS, homeostatic mechanisms mediating loss of appetite take effect. Conversely, under chronic inflammation in the hypothalamus as a response to HFD, mechanisms mediating a sustained ‘perpetual cycle' of appetite enhancement were observed. The GlyR protein may constitute a novel treatment target for the reduction of central orexigenic signals in obesity. PMID:27110685

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

PubMed

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

2016-01-30

Proteomic workflows based on nanoLC-MS/MS data-dependent-acquisition analysis have progressed tremendously in recent years. High-resolution and fast sequencing instruments have enabled the use of label-free quantitative methods, based either on spectral counting or on MS signal analysis, which appear as an attractive way to analyze differential protein expression in complex biological samples. However, the computational processing of the data for label-free quantification still remains a challenge. Here, we used a proteomic standard composed of an equimolar mixture of 48 human proteins (Sigma UPS1) spiked at different concentrations into a background of yeast cell lysate to benchmark several label-free quantitative workflows, involving different software packages developed in recent years. This experimental design allowed to finely assess their performances in terms of sensitivity and false discovery rate, by measuring the number of true and false-positive (respectively UPS1 or yeast background proteins found as differential). The spiked standard dataset has been deposited to the ProteomeXchange repository with the identifier PXD001819 and can be used to benchmark other label-free workflows, adjust software parameter settings, improve algorithms for extraction of the quantitative metrics from raw MS data, or evaluate downstream statistical methods. Bioinformatic pipelines for label-free quantitative analysis must be objectively evaluated in their ability to detect variant proteins with good sensitivity and low false discovery rate in large-scale proteomic studies. This can be done through the use of complex spiked samples, for which the "ground truth" of variant proteins is known, allowing a statistical evaluation of the performances of the data processing workflow. We provide here such a controlled standard dataset and used it to evaluate the performances of several label-free bioinformatics tools (including MaxQuant, Skyline, MFPaQ, IRMa-hEIDI and Scaffold) in different workflows, for detection of variant proteins with different absolute expression levels and fold change values. The dataset presented here can be useful for tuning software tool parameters, and also testing new algorithms for label-free quantitative analysis, or for evaluation of downstream statistical methods. Copyright © 2015 Elsevier B.V. All rights reserved.

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

PubMed

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

2016-08-11

Smoking is associated with several serious diseases, such as lung cancer and chronic obstructive pulmonary disease (COPD). Within our systems toxicology framework, we are assessing whether potential modified risk tobacco products (MRTP) can reduce smoking-related health risks compared to conventional cigarettes. In this article, we evaluated to what extent 2D-PAGE/MALDI MS/MS (2D-PAGE) can complement the iTRAQ LC-MS/MS results from a previously reported mouse inhalation study, in which we assessed a prototypic MRTP (pMRTP). Selected differentially expressed proteins identified by both LC-MS/MS and 2D-PAGE approaches were further verified using reverse-phase protein microarrays. LC-MS/MS captured the effects of cigarette smoke (CS) on the lung proteome more comprehensively than 2D-PAGE. However, an integrated analysis of both proteomics data sets showed that 2D-PAGE data complement the LC-MS/MS results by supporting the overall trend of lower effects of pMRTP aerosol than CS on the lung proteome. Biological effects of CS exposure supported by both methods included increases in immune-related, surfactant metabolism, proteasome, and actin cytoskeleton protein clusters. Overall, while 2D-PAGE has its value, especially as a complementary method for the analysis of effects on intact proteins, LC-MS/MS approaches will likely be the method of choice for proteome analysis in systems toxicology investigations. Quantitative proteomics is anticipated to play a growing role within systems toxicology assessment frameworks in the future. To further understand how different proteomics technologies can contribute to toxicity assessment, we conducted a quantitative proteomics analysis using 2D-PAGE and isobaric tag-based LC-MS/MS approaches and compared the results produced from the 2 approaches. Using a prototypic modified risk tobacco product (pMRTP) as our test item, we show compared with cigarette smoke, how 2D-PAGE results can complement and support LC-MS/MS data, demonstrating the much lower effects of pMRTP aerosol than cigarette smoke on the mouse lung proteome. The combined analysis of 2D-PAGE and LC-MS/MS data identified an effect of cigarette smoke on the proteasome and actin cytoskeleton in the lung. Copyright © 2016 The Authors. Published by Elsevier B.V. All rights reserved.

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.

Simulated linear test applied to quantitative proteomics.

PubMed

Pham, T V; Jimenez, C R

2016-09-01

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

Science, marketing and wishful thinking in quantitative proteomics.

PubMed

Hackett, Murray

2008-11-01

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

An FD-LC-MS/MS Proteomic Strategy for Revealing Cellular Protein Networks: A Conditional Superoxide Dismutase 1 Knockout Cells

PubMed Central

Ichibangase, Tomoko; Sugawara, Yasuhiro; Yamabe, Akio; Koshiyama, Akiyo; Yoshimura, Akari; Enomoto, Takemi; Imai, Kazuhiro

2012-01-01

Systems biology aims to understand biological phenomena in terms of complex biological and molecular interactions, and thus proteomics plays an important role in elucidating protein networks. However, many proteomic methods have suffered from their high variability, resulting in only showing altered protein names. Here, we propose a strategy for elucidating cellular protein networks based on an FD-LC-MS/MS proteomic method. The strategy permits reproducible relative quantitation of differences in protein levels between different cell populations and allows for integration of the data with those obtained through other methods. We demonstrate the validity of the approach through a comparison of differential protein expression in normal and conditional superoxide dismutase 1 gene knockout cells and believe that beginning with an FD-LC-MS/MS proteomic approach will enable researchers to elucidate protein networks more easily and comprehensively. PMID:23029042

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

PubMed Central

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

2015-01-01

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

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

PubMed Central

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

2015-01-01

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

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

PubMed Central

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

2012-01-01

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

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

Oestrus synchronisation and superovulation alter the cervicovaginal mucus proteome of the ewe.

PubMed

Maddison, Jessie W; Rickard, Jessica P; Bernecic, Naomi C; Tsikis, Guillaume; Soleilhavoup, Clement; Labas, Valerie; Combes-Soia, Lucie; Harichaux, Gregoire; Druart, Xavier; Leahy, Tamara; de Graaf, Simon P

2017-02-23

Although essential for artificial insemination (AI) and MOET (multiple ovulation and embryo transfer), oestrus synchronisation and superovulation are associated with increased female reproductive tract mucus production and altered sperm transport. The effects of such breeding practices on the ovine cervicovaginal (CV) mucus proteome have not been detailed. The aim of this study was to qualitatively and quantitatively investigate the Merino CV mucus proteome in naturally cycling (NAT) ewes at oestrus and mid-luteal phase, and quantitatively compare CV oestrus mucus proteomes of NAT, progesterone synchronised (P4) and superovulated (SOV) ewes. Quantitative analysis revealed 60 proteins were more abundant during oestrus and 127 were more abundant during the luteal phase, with 27 oestrus specific and 40 luteal specific proteins identified. The oestrus proteins most disparate in abundance compared to mid-luteal phase were ceruloplasmin (CP), chitinase-3-like protein 1 (CHI3L1), clusterin (CLU), alkaline phosphatase (ALPL) and mucin-16 (MUC16). Exogenous hormones greatly altered the proteome with 51 and 32 proteins more abundant and 98 and 53 proteins less abundant, in P4 and SOV mucus, respectively when compared to NAT mucus. Investigation of the impact of these proteomic changes on sperm motility and longevity within mucus may help improve sperm transport and fertility following cervical AI. This manuscript is the first to detail the proteome of ovine cervicovaginal mucus using qualitative and quantitative proteomic methods over the oestrous cycle in naturally cycling ewes, and also after application of common oestrus synchronisation and superovulation practices. The investigation of the mucus proteome throughout both the follicular and luteal periods of the oestrous cycle, and also after oestrous synchronisation and superovulation provides information about the endocrine control and the effects that exogenous hormones have on protein expression in the female reproductive tract. This information contributes to the field by providing important information on the changes that occur to the cervicovaginal mucus proteome after use of exogenous hormones in controlled breeding programs, which are commonly used on farm and also in a research setting. Copyright © 2017 Elsevier B.V. All rights reserved.

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

PubMed

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

2018-01-10

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

Embryology in the era of proteomics.

PubMed

Katz-Jaffe, Mandy G; McReynolds, Susanna

2013-03-15

Proteomic technologies have begun providing evidence that viable embryos possess unique protein profiles. Some of these potential protein biomarkers have been identified as extracellular and could be used in the development of a noninvasive quantitative method for embryo assessment. The field of assisted reproductive technologies would benefit from defining the human embryonic proteome and secretome, thereby expanding our current knowledge of embryonic cellular processes. Copyright © 2013 American Society for Reproductive Medicine. Published by Elsevier Inc. All rights reserved.

Proteomic analysis of acquired tamoxifen resistance in MCF-7 cells reveals expression signatures associated with enhanced migration

PubMed Central

2012-01-01

Introduction Acquired tamoxifen resistance involves complex signaling events that are not yet fully understood. Successful therapeutic intervention to delay the onset of hormone resistance depends critically on mechanistic elucidation of viable molecular targets associated with hormone resistance. This study was undertaken to investigate the global proteomic alterations in a tamoxifen resistant MCF-7 breast cancer cell line obtained by long term treatment of the wild type MCF-7 cell line with 4-hydroxytamoxifen (4-OH Tam). Methods We cultured MCF-7 cells with 4-OH Tam over a period of 12 months to obtain the resistant cell line. A gel-free, quantitative proteomic method was used to identify and quantify the proteome of the resistant cell line. Nano-flow high-performance liquid chromatography coupled to high resolution Fourier transform mass spectrometry was used to analyze fractionated peptide mixtures that were isobarically labeled from the resistant and control cell lysates. Real time quantitative PCR and Western blots were used to verify selected proteomic changes. Lentiviral vector transduction was used to generate MCF-7 cells stably expressing S100P. Online pathway analysis was performed to assess proteomic signatures in tamoxifen resistance. Survival analysis was done to evaluate clinical relevance of altered proteomic expressions. Results Quantitative proteomic analysis revealed a wide breadth of signaling events during transition to acquired tamoxifen resistance. A total of 629 proteins were found significantly changed with 364 up-regulated and 265 down-regulated. Collectively, these changes demonstrated the suppressed state of estrogen receptor (ER) and ER-regulated genes, activated survival signaling and increased migratory capacity of the resistant cell line. The protein S100P was found to play a critical role in conferring tamoxifen resistance and enhanced cell motility. Conclusions Our data demonstrate that the adaptive changes in the proteome of tamoxifen resistant breast cancer cells are characterized by down-regulated ER signaling, activation of alternative survival pathways, and enhanced cell motility through regulation of the actin cytoskeleton dynamics. Evidence also emerged that S100P mediates acquired tamoxifen resistance and migration capacity. PMID:22417809

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

PubMed Central

Zhang, Xi

2015-01-01

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

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

PubMed

Rigbolt, Kristoffer T G; Vanselow, Jens T; Blagoev, Blagoy

2011-08-01

Recent technological advances have made it possible to identify and quantify thousands of proteins in a single proteomics experiment. As a result of these developments, the analysis of data has become the bottleneck of proteomics experiment. To provide the proteomics community with a user-friendly platform for comprehensive analysis, inspection and visualization of quantitative proteomics data we developed the Graphical Proteomics Data Explorer (GProX)(1). The program requires no special bioinformatics training, as all functions of GProX are accessible within its graphical user-friendly interface which will be intuitive to most users. Basic features facilitate the uncomplicated management and organization of large data sets and complex experimental setups as well as the inspection and graphical plotting of quantitative data. These are complemented by readily available high-level analysis options such as database querying, clustering based on abundance ratios, feature enrichment tests for e.g. GO terms and pathway analysis tools. A number of plotting options for visualization of quantitative proteomics data is available and most analysis functions in GProX create customizable high quality graphical displays in both vector and bitmap formats. The generic import requirements allow data originating from essentially all mass spectrometry platforms, quantitation strategies and software to be analyzed in the program. GProX represents a powerful approach to proteomics data analysis providing proteomics experimenters with a toolbox for bioinformatics analysis of quantitative proteomics data. The program is released as open-source and can be freely downloaded from the project webpage at http://gprox.sourceforge.net.

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

PubMed Central

Rigbolt, Kristoffer T. G.; Vanselow, Jens T.; Blagoev, Blagoy

2011-01-01

Recent technological advances have made it possible to identify and quantify thousands of proteins in a single proteomics experiment. As a result of these developments, the analysis of data has become the bottleneck of proteomics experiment. To provide the proteomics community with a user-friendly platform for comprehensive analysis, inspection and visualization of quantitative proteomics data we developed the Graphical Proteomics Data Explorer (GProX)1. The program requires no special bioinformatics training, as all functions of GProX are accessible within its graphical user-friendly interface which will be intuitive to most users. Basic features facilitate the uncomplicated management and organization of large data sets and complex experimental setups as well as the inspection and graphical plotting of quantitative data. These are complemented by readily available high-level analysis options such as database querying, clustering based on abundance ratios, feature enrichment tests for e.g. GO terms and pathway analysis tools. A number of plotting options for visualization of quantitative proteomics data is available and most analysis functions in GProX create customizable high quality graphical displays in both vector and bitmap formats. The generic import requirements allow data originating from essentially all mass spectrometry platforms, quantitation strategies and software to be analyzed in the program. GProX represents a powerful approach to proteomics data analysis providing proteomics experimenters with a toolbox for bioinformatics analysis of quantitative proteomics data. The program is released as open-source and can be freely downloaded from the project webpage at http://gprox.sourceforge.net. PMID:21602510

Label-free protein profiling of formalin-fixed paraffin-embedded (FFPE) heart tissue reveals immediate mitochondrial impairment after ionising radiation.

PubMed

Azimzadeh, Omid; Scherthan, Harry; Yentrapalli, Ramesh; Barjaktarovic, Zarko; Ueffing, Marius; Conrad, Marcus; Neff, Frauke; Calzada-Wack, Julia; Aubele, Michaela; Buske, Christian; Atkinson, Michael J; Hauck, Stefanie M; Tapio, Soile

2012-04-18

Qualitative proteome profiling of formalin-fixed, paraffin-embedded (FFPE) tissue is advancing the field of clinical proteomics. However, quantitative proteome analysis of FFPE tissue is hampered by the lack of an efficient labelling method. The usage of conventional protein labelling on FFPE tissue has turned out to be inefficient. Classical labelling targets lysine residues that are blocked by the formalin treatment. The aim of this study was to establish a quantitative proteomics analysis of FFPE tissue by combining the label-free approach with optimised protein extraction and separation conditions. As a model system we used FFPE heart tissue of control and exposed C57BL/6 mice after total body irradiation using a gamma ray dose of 3 gray. We identified 32 deregulated proteins (p≤0.05) in irradiated hearts 24h after the exposure. The proteomics data were further evaluated and validated by bioinformatics and immunoblotting investigation. In good agreement with our previous results using fresh-frozen tissue, the analysis indicated radiation-induced alterations in three main biological pathways: respiratory chain, lipid metabolism and pyruvate metabolism. The label-free approach enables the quantitative measurement of radiation-induced alterations in FFPE tissue and facilitates retrospective biomarker identification using clinical archives. Copyright © 2012 Elsevier B.V. All rights reserved.

Find Pairs: The Module for Protein Quantification of the PeakQuant Software Suite

PubMed Central

Eisenacher, Martin; Kohl, Michael; Wiese, Sebastian; Hebeler, Romano; Meyer, Helmut E.

2012-01-01

Abstract Accurate quantification of proteins is one of the major tasks in current proteomics research. To address this issue, a wide range of stable isotope labeling techniques have been developed, allowing one to quantitatively study thousands of proteins by means of mass spectrometry. In this article, the FindPairs module of the PeakQuant software suite is detailed. It facilitates the automatic determination of protein abundance ratios based on the automated analysis of stable isotope-coded mass spectrometric data. Furthermore, it implements statistical methods to determine outliers due to biological as well as technical variance of proteome data obtained in replicate experiments. This provides an important means to evaluate the significance in obtained protein expression data. For demonstrating the high applicability of FindPairs, we focused on the quantitative analysis of proteome data acquired in 14N/15N labeling experiments. We further provide a comprehensive overview of the features of the FindPairs software, and compare these with existing quantification packages. The software presented here supports a wide range of proteomics applications, allowing one to quantitatively assess data derived from different stable isotope labeling approaches, such as 14N/15N labeling, SILAC, and iTRAQ. The software is publicly available at http://www.medizinisches-proteom-center.de/software and free for academic use. PMID:22909347

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

PubMed

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

2013-12-01

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

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

PubMed

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

2017-01-01

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

Platform-independent and label-free quantitation of proteomic data using MS1 extracted ion chromatograms in skyline: application to protein acetylation and phosphorylation.

PubMed

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

2012-05-01

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

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

PubMed Central

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

2012-01-01

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

Quantitative proteomics in cardiovascular research: global and targeted strategies

PubMed Central

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

2014-01-01

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

Design and analysis issues in quantitative proteomics studies.

PubMed

Karp, Natasha A; Lilley, Kathryn S

2007-09-01

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

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

PubMed

Csősz, Éva; Kalló, Gergő; Márkus, Bernadett; Deák, Eszter; Csutak, Adrienne; Tőzsér, József

2017-02-05

Identification of new biomarkers specific for various pathological conditions is an important field in medical sciences. Body fluids have emerging potential in biomarker studies especially those which are continuously available and can be collected by non-invasive means. Changes in the protein composition of body fluids such as tears, saliva, sweat, etc. may provide information on both local and systemic conditions of medical relevance. In this review, our aim is to discuss the quantitative proteomics techniques used in biomarker studies, and to present advances in quantitative body fluid proteomics of non-invasively collectable body fluids with relevance to biomarker identification. The advantages and limitations of the widely used quantitative proteomics techniques are also presented. Based on the reviewed literature, we suggest an ideal pipeline for body fluid analyses aiming at biomarkers discoveries: starting from identification of biomarker candidates by shotgun quantitative proteomics or protein arrays, through verification of potential biomarkers by targeted mass spectrometry, to the antibody-based validation of biomarkers. The importance of body fluids as a rich source of biomarkers is discussed. Quantitative proteomics is a challenging part of proteomics applications. The body fluids collected by non-invasive means have high relevance in medicine; they are good sources for biomarkers used in establishing the diagnosis, follow up of disease progression and predicting high risk groups. The review presents the most widely used quantitative proteomics techniques in body fluid analysis and lists the potential biomarkers identified in tears, saliva, sweat, nasal mucus and urine for local and systemic diseases. Copyright © 2016 Elsevier B.V. All rights reserved.

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

PubMed

Zhang, Xi

2015-09-01

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

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

PubMed Central

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

2011-01-01

The use of quantitative proteomics methods to study protein complexes has the potential to provide in-depth information on the abundance of different protein components as well as their modification state in various cellular conditions. To interrogate protein complex quantitation using shotgun proteomic methods, we have focused on the analysis of protein complexes using label-free multidimensional protein identification technology and studied the reproducibility of biological replicates. For these studies, we focused on three highly related and essential multi-protein enzymes, RNA polymerase I, II, and III from Saccharomyces cerevisiae. We found that label-free quantitation using spectral counting is highly reproducible at the protein and peptide level when analyzing RNA polymerase I, II, and III. In addition, we show that peptide sampling does not follow a random sampling model, and we show the need for advanced computational models to predict peptide detection probabilities. In order to address these issues, we used the APEX protocol to model the expected peptide detectability based on whole cell lysate acquired using the same multidimensional protein identification technology analysis used for the protein complexes. Neither method was able to predict the peptide sampling levels that we observed using replicate multidimensional protein identification technology analyses. In addition to the analysis of the RNA polymerase complexes, our analysis provides quantitative information about several RNAP associated proteins including the RNAPII elongation factor complexes DSIF and TFIIF. Our data shows that DSIF and TFIIF are the most highly enriched RNAP accessory factors in Rpb3-TAP purifications and demonstrate our ability to measure low level associated protein abundance across biological replicates. In addition, our quantitative data supports a model in which DSIF and TFIIF interact with RNAPII in a dynamic fashion in agreement with previously published reports. PMID:21048197

Plant proteome analysis: a 2006 update.

PubMed

Jorrín, Jesús V; Maldonado, Ana M; Castillejo, Ma Angeles

2007-08-01

This 2006 'Plant Proteomics Update' is a continuation of the two previously published in 'Proteomics' by 2004 (Canovas et al., Proteomics 2004, 4, 285-298) and 2006 (Rossignol et al., Proteomics 2006, 6, 5529-5548) and it aims to bring up-to-date the contribution of proteomics to plant biology on the basis of the original research papers published throughout 2006, with references to those appearing last year. According to the published papers and topics addressed, we can conclude that, as observed for the three previous years, there has been a quantitative, but not qualitative leap in plant proteomics. The full potential of proteomics is far from being exploited in plant biology research, especially if compared to other organisms, mainly yeast and humans, and a number of challenges, mainly technological, remain to be tackled. The original papers published last year numbered nearly 100 and deal with the proteome of at least 26 plant species, with a high percentage for Arabidopsis thaliana (28) and rice (11). Scientific objectives ranged from proteomic analysis of organs/tissues/cell suspensions (57) or subcellular fractions (29), to the study of plant development (12), the effect of hormones and signalling molecules (8) and response to symbionts (4) and stresses (27). A small number of contributions have covered PTMs (8) and protein interactions (4). 2-DE (specifically IEF-SDS-PAGE) coupled to MS still constitutes the almost unique platform utilized in plant proteome analysis. The application of gel-free protein separation methods and 'second generation' proteomic techniques such as multidimensional protein identification technology (MudPIT), and those for quantitative proteomics including DIGE, isotope-coded affinity tags (ICAT), iTRAQ and stable isotope labelling by amino acids in cell culture (SILAC) still remains anecdotal. This review is divided into seven sections: Introduction, Methodology, Subcellular proteomes, Development, Responses to biotic and abiotic stresses, PTMs and Protein interactions. Section 8 summarizes the major pitfalls and challenges of plant proteomics.

Proteomes and Phosphoproteomes of Anther and Pollen: Availability and Progress.

PubMed

Zhang, Zaibao; Hu, Menghui; Feng, Xiaobing; Gong, Andong; Cheng, Lin; Yuan, Hongyu

2017-10-01

In flowering plants, anther development plays crucial role in sexual reproduction. Within the anther, microspore mother cells meiosis produces microspores, which further develop into pollen grains that play decisive role in plant reproduction. Previous studies on anther biology mainly focused on single gene functions relying on genetic and molecular methods. Recently, anther development has been expanded from multiple OMICS approaches like transcriptomics, proteomics/phosphoproteomics, and metabolomics. The development of proteomics techniques allowing increased proteome coverage and quantitative measurements of proteins which can characterize proteomes and their modulation during normal development, biotic and abiotic stresses in anther development. In this review, we summarize the achievements of proteomics and phosphoproteomics with anther and pollen organs from model plant and crop species (i.e. Arabidopsis, rice, tobacco). The increased proteomic information facilitated translation of information from the models to crops and thus aid in agricultural improvement. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Mspire-Simulator: LC-MS shotgun proteomic simulator for creating realistic gold standard data.

PubMed

Noyce, Andrew B; Smith, Rob; Dalgleish, James; Taylor, Ryan M; Erb, K C; Okuda, Nozomu; Prince, John T

2013-12-06

The most important step in any quantitative proteomic pipeline is feature detection (aka peak picking). However, generating quality hand-annotated data sets to validate the algorithms, especially for lower abundance peaks, is nearly impossible. An alternative for creating gold standard data is to simulate it with features closely mimicking real data. We present Mspire-Simulator, a free, open-source shotgun proteomic simulator that goes beyond previous simulation attempts by generating LC-MS features with realistic m/z and intensity variance along with other noise components. It also includes machine-learned models for retention time and peak intensity prediction and a genetic algorithm to custom fit model parameters for experimental data sets. We show that these methods are applicable to data from three different mass spectrometers, including two fundamentally different types, and show visually and analytically that simulated peaks are nearly indistinguishable from actual data. Researchers can use simulated data to rigorously test quantitation software, and proteomic researchers may benefit from overlaying simulated data on actual data sets.

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.

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

PubMed

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

2016-10-07

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

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.

Hypothalamus proteomics from mouse models with obesity and anorexia reveals therapeutic targets of appetite regulation.

PubMed

Manousopoulou, A; Koutmani, Y; Karaliota, S; Woelk, C H; Manolakos, E S; Karalis, K; Garbis, S D

2016-04-25

This study examined the proteomic profile of the hypothalamus in mice exposed to a high-fat diet (HFD) or with the anorexia of acute illness. This comparison could provide insight on the effects of these two opposite states of energy balance on appetite regulation. Four to six-week-old male C56BL/6J mice were fed a normal (control 1 group; n=7) or a HFD (HFD group; n=10) for 8 weeks. The control 2 (n=7) and lipopolysaccharide (LPS) groups (n=10) were fed a normal diet for 8 weeks before receiving an injection of saline and LPS, respectively. Hypothalamic regions were analysed using a quantitative proteomics method based on a combination of techniques including iTRAQ stable isotope labeling, orthogonal two-dimensional liquid chromatography hyphenated with nanospray ionization and high-resolution mass spectrometry. Key proteins were validated with quantitative PCR. Quantitative proteomics of the hypothalamous regions profiled a total of 9249 protein groups (q<0.05). Of these, 7718 protein groups were profiled with a minimum of two unique peptides for each. Hierachical clustering of the differentiated proteome revealed distinct proteomic signatures for the hypothalamus under the HFD and LPS nutritional conditions. Literature research with in silico bioinformatics interpretation of the differentiated proteome identified key biological relevant proteins and implicated pathways. Furthermore, the study identified potential pharmacologic targets. In the LPS groups, the anorexigen pro-opiomelanocortin was downregulated. In mice with obesity, nuclear factor-κB, glycine receptor subunit alpha-4 (GlyR) and neuropeptide Y levels were elevated, whereas serotonin receptor 1B levels decreased. High-precision quantitative proteomics revealed that under acute systemic inflammation in the hypothalamus as a response to LPS, homeostatic mechanisms mediating loss of appetite take effect. Conversely, under chronic inflammation in the hypothalamus as a response to HFD, mechanisms mediating a sustained 'perpetual cycle' of appetite enhancement were observed. The GlyR protein may constitute a novel treatment target for the reduction of central orexigenic signals in obesity.

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

PubMed

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

2011-04-01

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

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

PubMed

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

2006-08-01

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

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.

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.

Bioinformatics for spermatogenesis: annotation of male reproduction based on proteomics

PubMed Central

Zhou, Tao; Zhou, Zuo-Min; Guo, Xue-Jiang

2013-01-01

Proteomics strategies have been widely used in the field of male reproduction, both in basic and clinical research. Bioinformatics methods are indispensable in proteomics-based studies and are used for data presentation, database construction and functional annotation. In the present review, we focus on the functional annotation of gene lists obtained through qualitative or quantitative methods, summarizing the common and male reproduction specialized proteomics databases. We introduce several integrated tools used to find the hidden biological significance from the data obtained. We further describe in detail the information on male reproduction derived from Gene Ontology analyses, pathway analyses and biomedical analyses. We provide an overview of bioinformatics annotations in spermatogenesis, from gene function to biological function and from biological function to clinical application. On the basis of recently published proteomics studies and associated data, we show that bioinformatics methods help us to discover drug targets for sperm motility and to scan for cancer-testis genes. In addition, we summarize the online resources relevant to male reproduction research for the exploration of the regulation of spermatogenesis. PMID:23852026

Toxicoproteomics in Aquatic Toxicology: iTRAQ Reveals Insight into Proteins Affected by 17alpha-ethinylestradiol, Dieldrin, and 17â-trenbolone

EPA Science Inventory

Toxicoproteomics is an emerging discipline in toxicology for characterizing chemical modes of action at the molecular level. We have successfully utilized a quantitative proteomics method termed isobaric tagging for relative and absolute quantitation (iTRAQ) to measure protein re...

RECENT ADVANCES IN QUANTITATIVE NEUROPROTEOMICS

PubMed Central

Craft, George E; Chen, Anshu; Nairn, Angus C

2014-01-01

The field of proteomics is undergoing rapid development in a number of different areas including improvements in mass spectrometric platforms, peptide identification algorithms and bioinformatics. In particular, new and/or improved approaches have established robust methods that not only allow for in-depth and accurate peptide and protein identification and modification, but also allow for sensitive measurement of relative or absolute quantitation. These methods are beginning to be applied to the area of neuroproteomics, but the central nervous system poses many specific challenges in terms of quantitative proteomics, given the large number of different neuronal cell types that are intermixed and that exhibit distinct patterns of gene and protein expression. This review highlights the recent advances that have been made in quantitative neuroproteomics, with a focus on work published over the last five years that applies emerging methods to normal brain function as well as to various neuropsychiatric disorders including schizophrenia and drug addiction as well as of neurodegenerative diseases including Parkinson’s disease and Alzheimer’s disease. While older methods such as two-dimensional polyacrylamide electrophoresis continued to be used, a variety of more in-depth MS-based approaches including both label (ICAT, iTRAQ, TMT, SILAC, SILAM), label-free (label-free, MRM, SWATH) and absolute quantification methods, are rapidly being applied to neurobiological investigations of normal and diseased brain tissue as well as of cerebrospinal fluid (CSF). While the biological implications of many of these studies remain to be clearly established, that there is a clear need for standardization of experimental design and data analysis, and that the analysis of protein changes in specific neuronal cell types in the central nervous system remains a serious challenge, it appears that the quality and depth of the more recent quantitative proteomics studies is beginning to shed light on a number of aspects of neuroscience that relates to normal brain function as well as of the changes in protein expression and regulation that occurs in neuropsychiatric and neurodegenerative disorders. PMID:23623823

Recent advances in quantitative neuroproteomics.

PubMed

Craft, George E; Chen, Anshu; Nairn, Angus C

2013-06-15

The field of proteomics is undergoing rapid development in a number of different areas including improvements in mass spectrometric platforms, peptide identification algorithms and bioinformatics. In particular, new and/or improved approaches have established robust methods that not only allow for in-depth and accurate peptide and protein identification and modification, but also allow for sensitive measurement of relative or absolute quantitation. These methods are beginning to be applied to the area of neuroproteomics, but the central nervous system poses many specific challenges in terms of quantitative proteomics, given the large number of different neuronal cell types that are intermixed and that exhibit distinct patterns of gene and protein expression. This review highlights the recent advances that have been made in quantitative neuroproteomics, with a focus on work published over the last five years that applies emerging methods to normal brain function as well as to various neuropsychiatric disorders including schizophrenia and drug addiction as well as of neurodegenerative diseases including Parkinson's disease and Alzheimer's disease. While older methods such as two-dimensional polyacrylamide electrophoresis continued to be used, a variety of more in-depth MS-based approaches including both label (ICAT, iTRAQ, TMT, SILAC, SILAM), label-free (label-free, MRM, SWATH) and absolute quantification methods, are rapidly being applied to neurobiological investigations of normal and diseased brain tissue as well as of cerebrospinal fluid (CSF). While the biological implications of many of these studies remain to be clearly established, that there is a clear need for standardization of experimental design and data analysis, and that the analysis of protein changes in specific neuronal cell types in the central nervous system remains a serious challenge, it appears that the quality and depth of the more recent quantitative proteomics studies is beginning to shed light on a number of aspects of neuroscience that relates to normal brain function as well as of the changes in protein expression and regulation that occurs in neuropsychiatric and neurodegenerative disorders. Copyright © 2013. Published by Elsevier Inc.

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

PubMed

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

2016-06-03

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

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.

A Routine 'Top-Down' Approach to Analysis of the Human Serum Proteome.

PubMed

D'Silva, Arlene M; Hyett, Jon A; Coorssen, Jens R

2017-06-06

Serum provides a rich source of potential biomarker proteoforms. One of the major obstacles in analysing serum proteomes is detecting lower abundance proteins owing to the presence of hyper-abundant species (e.g., serum albumin and immunoglobulins). Although depletion methods have been used to address this, these can lead to the concomitant removal of non-targeted protein species, and thus raise issues of specificity, reproducibility, and the capacity for meaningful quantitative analyses. Altering the native stoichiometry of the proteome components may thus yield a more complex series of issues than dealing directly with the inherent complexity of the sample. Hence, here we targeted method refinements so as to ensure optimum resolution of serum proteomes via a top down two-dimensional gel electrophoresis (2DE) approach that enables the routine assessment of proteoforms and is fully compatible with subsequent mass spectrometric analyses. Testing included various fractionation and non-fractionation approaches. The data show that resolving 500 µg protein on 17 cm 3-10 non-linear immobilised pH gradient strips in the first dimension followed by second dimension resolution on 7-20% gradient gels with a combination of lithium dodecyl sulfate (LDS) and sodium dodecyl sulfate (SDS) detergents markedly improves the resolution and detection of proteoforms in serum. In addition, well established third dimension electrophoretic separations in combination with deep imaging further contributed to the best available resolution, detection, and thus quantitative top-down analysis of serum proteomes.

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.

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.

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.

Global Cell Proteome Profiling, Phospho-signaling and Quantitative 
Proteomics for Identification of New Biomarkers in Acute Myeloid 
Leukemia Patients

PubMed Central

Aasebø, Elise; Forthun, Rakel B.; Berven, Frode; Selheim, Frode; Hernandez-Valladares, Maria

2016-01-01

The identification of protein biomarkers for acute myeloid leukemia (AML) that could find applications in AML diagnosis and prognosis, treatment and the selection for bone marrow transplant requires substantial comparative analyses of the proteomes from AML patients. In the past years, several studies have suggested some biomarkers for AML diagnosis or AML classification using methods for sample preparation with low proteome coverage and low resolution mass spectrometers. However, most of the studies did not follow up, confirm or validate their candidates with more patient samples. Current proteomics methods, new high resolution and fast mass spectrometers allow the identification and quantification of several thousands of proteins obtained from few tens of μg of AML cell lysate. Enrichment methods for posttranslational modifications (PTM), such as phosphorylation, can isolate several thousands of site-specific phosphorylated peptides from AML patient samples, which subsequently can be quantified with high confidence in new mass spectrometers. While recent reports aiming to propose proteomic or phosphoproteomic biomarkers on the studied AML patient samples have taken advantage of the technological progress, the access to large cohorts of AML patients to sample from and the availability of appropriate control samples still remain challenging. PMID:26306748

Methods, Tools and Current Perspectives in Proteogenomics *

PubMed Central

Ruggles, Kelly V.; Krug, Karsten; Wang, Xiaojing; Clauser, Karl R.; Wang, Jing; Payne, Samuel H.; Fenyö, David; Zhang, Bing; Mani, D. R.

2017-01-01

With combined technological advancements in high-throughput next-generation sequencing and deep mass spectrometry-based proteomics, proteogenomics, i.e. the integrative analysis of proteomic and genomic data, has emerged as a new research field. Early efforts in the field were focused on improving protein identification using sample-specific genomic and transcriptomic sequencing data. More recently, integrative analysis of quantitative measurements from genomic and proteomic studies have identified novel insights into gene expression regulation, cell signaling, and disease. Many methods and tools have been developed or adapted to enable an array of integrative proteogenomic approaches and in this article, we systematically classify published methods and tools into four major categories, (1) Sequence-centric proteogenomics; (2) Analysis of proteogenomic relationships; (3) Integrative modeling of proteogenomic data; and (4) Data sharing and visualization. We provide a comprehensive review of methods and available tools in each category and highlight their typical applications. PMID:28456751

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.

Proteomic profiling of an undefined microbial consortium cultured in fermented dairy manure: Methods development.

PubMed

Hanson, Andrea J; Paszczynski, Andrzej J; Coats, Erik R

2016-03-01

The production of polyhydroxyalkanoates (PHA; bioplastics) from waste or surplus feedstocks using mixed microbial consortia (MMC) and aerobic dynamic feeding (ADF) is a growing field within mixed culture biotechnology. This study aimed to optimize a 2DE workflow to investigate the proteome dynamics of an MMC synthesizing PHA from fermented dairy manure. To mitigate the challenges posed to effective 2DE by this complex sample matrix, the bacterial biomass was purified using Accudenz gradient centrifugation (AGC) before protein extraction. The optimized 2DE method yielded high-quality gels suitable for quantitative comparative analysis and subsequent protein identification by LC-MS/MS. The optimized 2DE method could be adapted to other proteomic investigations involving MMC in complex organic or environmental matrices. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

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

PubMed

Ohtsuki, Sumio; Hirayama, Mio; Ito, Shingo; Uchida, Yasuo; Tachikawa, Masanori; Terasaki, Tetsuya

2014-06-01

The blood-brain barrier (BBB) is formed by brain capillary endothelial cells linked together via complex tight junctions, and serves to prevent entry of drugs into the brain. Multiple transporters are expressed at the BBB, where they control exchange of materials between the circulating blood and brain interstitial fluid, thereby supporting and protecting the CNS. An understanding of the BBB is necessary for efficient development of CNS-acting drugs and to identify potential drug targets for treatment of CNS diseases. Quantitative targeted proteomics can provide detailed information on protein expression levels at the BBB. The present review highlights the latest applications of quantitative targeted proteomics in BBB research, specifically to evaluate species and in vivo-in vitro differences, and to reconstruct in vivo transport activity. Such a BBB quantitative proteomics approach can be considered as pharmacoproteomics.

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

PubMed Central

2015-01-01

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

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.

Advances in Quantitative Proteomics of Microbes and Microbial Communities

NASA Astrophysics Data System (ADS)

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

2015-12-01

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

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

PubMed Central

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

2016-01-01

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

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.

Accurate proteome-wide protein quantification from high-resolution 15N mass spectra

PubMed Central

2011-01-01

In quantitative mass spectrometry-based proteomics, the metabolic incorporation of a single source of 15N-labeled nitrogen has many advantages over using stable isotope-labeled amino acids. However, the lack of a robust computational framework for analyzing the resulting spectra has impeded wide use of this approach. We have addressed this challenge by introducing a new computational methodology for analyzing 15N spectra in which quantification is integrated with identification. Application of this method to an Escherichia coli growth transition reveals significant improvement in quantification accuracy over previous methods. PMID:22182234

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

PubMed

Gizak, Agnieszka; Rakus, Dariusz

2016-01-11

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

C-STrap Sample Preparation Method--In-Situ Cysteinyl Peptide Capture for Bottom-Up Proteomics Analysis in the STrap Format.

PubMed

Zougman, Alexandre; Banks, Rosamonde E

2015-01-01

Recently we introduced the concept of Suspension Trapping (STrap) for bottom-up proteomics sample processing that is based upon SDS-mediated protein extraction, swift detergent removal and rapid reactor-type protein digestion in a quartz depth filter trap. As the depth filter surface is made of silica, it is readily modifiable with various functional groups using the silane coupling chemistries. Thus, during the digest, peptides possessing specific features could be targeted for enrichment by the functionalized depth filter material while non-targeted peptides could be collected as an unbound distinct fraction after the digest. In the example presented here the quartz depth filter surface is functionalized with the pyridyldithiol group therefore enabling reversible in-situ capture of the cysteine-containing peptides generated during the STrap-based digest. The described C-STrap method retains all advantages of the original STrap methodology and provides robust foundation for the conception of the targeted in-situ peptide fractionation in the STrap format for bottom-up proteomics. The presented data support the method's use in qualitative and semi-quantitative proteomics experiments.

Multiple testing corrections in quantitative proteomics: A useful but blunt tool.

PubMed

Pascovici, Dana; Handler, David C L; Wu, Jemma X; Haynes, Paul A

2016-09-01

Multiple testing corrections are a useful tool for restricting the FDR, but can be blunt in the context of low power, as we demonstrate by a series of simple simulations. Unfortunately, in proteomics experiments low power can be common, driven by proteomics-specific issues like small effects due to ratio compression, and few replicates due to reagent high cost, instrument time availability and other issues; in such situations, most multiple testing corrections methods, if used with conventional thresholds, will fail to detect any true positives even when many exist. In this low power, medium scale situation, other methods such as effect size considerations or peptide-level calculations may be a more effective option, even if they do not offer the same theoretical guarantee of a low FDR. Thus, we aim to highlight in this article that proteomics presents some specific challenges to the standard multiple testing corrections methods, which should be employed as a useful tool but not be regarded as a required rubber stamp. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

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.

Protein identification and quantification from riverbank grape, Vitis riparia: Comparing SDS-PAGE and FASP-GPF techniques for shotgun proteomic analysis.

PubMed

George, Iniga S; Fennell, Anne Y; Haynes, Paul A

2015-09-01

Protein sample preparation optimisation is critical for establishing reproducible high throughput proteomic analysis. In this study, two different fractionation sample preparation techniques (in-gel digestion and in-solution digestion) for shotgun proteomics were used to quantitatively compare proteins identified in Vitis riparia leaf samples. The total number of proteins and peptides identified were compared between filter aided sample preparation (FASP) coupled with gas phase fractionation (GPF) and SDS-PAGE methods. There was a 24% increase in the total number of reproducibly identified proteins when FASP-GPF was used. FASP-GPF is more reproducible, less expensive and a better method than SDS-PAGE for shotgun proteomics of grapevine samples as it significantly increases protein identification across biological replicates. Total peptide and protein information from the two fractionation techniques is available in PRIDE with the identifier PXD001399 (http://proteomecentral.proteomexchange.org/dataset/PXD001399). © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

A draft map of the mouse pluripotent stem cell spatial proteome

PubMed Central

Christoforou, Andy; Mulvey, Claire M.; Breckels, Lisa M.; Geladaki, Aikaterini; Hurrell, Tracey; Hayward, Penelope C.; Naake, Thomas; Gatto, Laurent; Viner, Rosa; Arias, Alfonso Martinez; Lilley, Kathryn S.

2016-01-01

Knowledge of the subcellular distribution of proteins is vital for understanding cellular mechanisms. Capturing the subcellular proteome in a single experiment has proven challenging, with studies focusing on specific compartments or assigning proteins to subcellular niches with low resolution and/or accuracy. Here we introduce hyperLOPIT, a method that couples extensive fractionation, quantitative high-resolution accurate mass spectrometry with multivariate data analysis. We apply hyperLOPIT to a pluripotent stem cell population whose subcellular proteome has not been extensively studied. We provide localization data on over 5,000 proteins with unprecedented spatial resolution to reveal the organization of organelles, sub-organellar compartments, protein complexes, functional networks and steady-state dynamics of proteins and unexpected subcellular locations. The method paves the way for characterizing the impact of post-transcriptional and post-translational modification on protein location and studies involving proteome-level locational changes on cellular perturbation. An interactive open-source resource is presented that enables exploration of these data. PMID:26754106

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

PubMed

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

2013-09-06

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

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

PubMed Central

2013-01-01

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

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

PubMed

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

2013-12-16

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

Automated selected reaction monitoring software for accurate label-free protein quantification.

PubMed

Teleman, Johan; Karlsson, Christofer; Waldemarson, Sofia; Hansson, Karin; James, Peter; Malmström, Johan; Levander, Fredrik

2012-07-06

Selected reaction monitoring (SRM) is a mass spectrometry method with documented ability to quantify proteins accurately and reproducibly using labeled reference peptides. However, the use of labeled reference peptides becomes impractical if large numbers of peptides are targeted and when high flexibility is desired when selecting peptides. We have developed a label-free quantitative SRM workflow that relies on a new automated algorithm, Anubis, for accurate peak detection. Anubis efficiently removes interfering signals from contaminating peptides to estimate the true signal of the targeted peptides. We evaluated the algorithm on a published multisite data set and achieved results in line with manual data analysis. In complex peptide mixtures from whole proteome digests of Streptococcus pyogenes we achieved a technical variability across the entire proteome abundance range of 6.5-19.2%, which was considerably below the total variation across biological samples. Our results show that the label-free SRM workflow with automated data analysis is feasible for large-scale biological studies, opening up new possibilities for quantitative proteomics and systems biology.

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.

Global, quantitative and dynamic mapping of protein subcellular localization.

PubMed

Itzhak, Daniel N; Tyanova, Stefka; Cox, Jürgen; Borner, Georg Hh

2016-06-09

Subcellular localization critically influences protein function, and cells control protein localization to regulate biological processes. We have developed and applied Dynamic Organellar Maps, a proteomic method that allows global mapping of protein translocation events. We initially used maps statically to generate a database with localization and absolute copy number information for over 8700 proteins from HeLa cells, approaching comprehensive coverage. All major organelles were resolved, with exceptional prediction accuracy (estimated at >92%). Combining spatial and abundance information yielded an unprecedented quantitative view of HeLa cell anatomy and organellar composition, at the protein level. We subsequently demonstrated the dynamic capabilities of the approach by capturing translocation events following EGF stimulation, which we integrated into a quantitative model. Dynamic Organellar Maps enable the proteome-wide analysis of physiological protein movements, without requiring any reagents specific to the investigated process, and will thus be widely applicable in cell biology.

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

PubMed

Yu, Kebing; Salomon, Arthur R

2009-12-01

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

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.

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

PubMed

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

2015-08-01

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

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

PubMed

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

2012-03-01

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

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

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

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

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

A new dimethyl labeling-based SID-MRM-MS method and its application to three proteases involved in insulin maturation.

PubMed

Cheng, Dongwan; Zheng, Li; Hou, Junjie; Wang, Jifeng; Xue, Peng; Yang, Fuquan; Xu, Tao

2015-01-01

The absolute quantification of target proteins in proteomics involves stable isotope dilution coupled with multiple reactions monitoring mass spectrometry (SID-MRM-MS). The successful preparation of stable isotope-labeled internal standard peptides is an important prerequisite for the SID-MRM absolute quantification methods. Dimethyl labeling has been widely used in relative quantitative proteomics and it is fast, simple, reliable, cost-effective, and applicable to any protein sample, making it an ideal candidate method for the preparation of stable isotope-labeled internal standards. MRM mass spectrometry is of high sensitivity, specificity, and throughput characteristics and can quantify multiple proteins simultaneously, including low-abundance proteins in precious samples such as pancreatic islets. In this study, a new method for the absolute quantification of three proteases involved in insulin maturation, namely PC1/3, PC2 and CPE, was developed by coupling a stable isotope dimethyl labeling strategy for internal standard peptide preparation with SID-MRM-MS quantitative technology. This method offers a new and effective approach for deep understanding of the functional status of pancreatic β cells and pathogenesis in diabetes.

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

PubMed

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

2018-03-01

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

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

PubMed

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

2016-01-29

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

Targeted quantitative analysis of Streptococcus pyogenes virulence factors by multiple reaction monitoring.

PubMed

Lange, Vinzenz; Malmström, Johan A; Didion, John; King, Nichole L; Johansson, Björn P; Schäfer, Juliane; Rameseder, Jonathan; Wong, Chee-Hong; Deutsch, Eric W; Brusniak, Mi-Youn; Bühlmann, Peter; Björck, Lars; Domon, Bruno; Aebersold, Ruedi

2008-08-01

In many studies, particularly in the field of systems biology, it is essential that identical protein sets are precisely quantified in multiple samples such as those representing differentially perturbed cell states. The high degree of reproducibility required for such experiments has not been achieved by classical mass spectrometry-based proteomics methods. In this study we describe the implementation of a targeted quantitative approach by which predetermined protein sets are first identified and subsequently quantified at high sensitivity reliably in multiple samples. This approach consists of three steps. First, the proteome is extensively mapped out by multidimensional fractionation and tandem mass spectrometry, and the data generated are assembled in the PeptideAtlas database. Second, based on this proteome map, peptides uniquely identifying the proteins of interest, proteotypic peptides, are selected, and multiple reaction monitoring (MRM) transitions are established and validated by MS2 spectrum acquisition. This process of peptide selection, transition selection, and validation is supported by a suite of software tools, TIQAM (Targeted Identification for Quantitative Analysis by MRM), described in this study. Third, the selected target protein set is quantified in multiple samples by MRM. Applying this approach we were able to reliably quantify low abundance virulence factors from cultures of the human pathogen Streptococcus pyogenes exposed to increasing amounts of plasma. The resulting quantitative protein patterns enabled us to clearly define the subset of virulence proteins that is regulated upon plasma exposure.

Statistical design of quantitative mass spectrometry-based proteomic experiments.

PubMed

Oberg, Ann L; Vitek, Olga

2009-05-01

We review the fundamental principles of statistical experimental design, and their application to quantitative mass spectrometry-based proteomics. We focus on class comparison using Analysis of Variance (ANOVA), and discuss how randomization, replication and blocking help avoid systematic biases due to the experimental procedure, and help optimize our ability to detect true quantitative changes between groups. We also discuss the issues of pooling multiple biological specimens for a single mass analysis, and calculation of the number of replicates in a future study. When applicable, we emphasize the parallels between designing quantitative proteomic experiments and experiments with gene expression microarrays, and give examples from that area of research. We illustrate the discussion using theoretical considerations, and using real-data examples of profiling of disease.

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

PubMed

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

2014-03-07

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

An effective protein extraction method for two-dimensional electrophoresis in the anticancer herb Andrographis paniculata Nees.

PubMed

Talei, Daryush; Valdiani, Alireza; Puad, Mohd Abdullah

2013-01-01

Proteomic analysis of plants relies on high yields of pure protein. In plants, protein extraction and purification present a great challenge due to accumulation of a large amount of interfering substances, including polysaccharides, polyphenols, and secondary metabolites. Therefore, it is necessary to modify the extraction protocols. A study was conducted to compare four protein extraction and precipitation methods for proteomic analysis. The results showed significant differences in protein content among the four methods. The chloroform-trichloroacetic acid-acetone method using 4-(2-hydroxyethyl)-1-piperazineethanesulfonic acid (HEPES) buffer provided the best results in terms of protein content, pellets, spot resolution, and intensity of unique spots detected. An overall of 83 qualitative or quantitative significant differential spots were found among the four methods. Based on the 2-DE gel map, the method is expected to benefit the development of high-level proteomic and biochemical studies of Andrographis paniculata, which may also be applied to other recalcitrant medicinal plant tissues. © 2013 International Union of Biochemistry and Molecular Biology, Inc.

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

PubMed

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

2011-10-01

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

Proteomic Analysis of Serum from Patients with Major Depressive Disorder to Compare Their Depressive and Remission Statuses

PubMed Central

Lee, Jiyeong; Joo, Eun-Jeong; Lim, Hee-Joung; Park, Jong-Moon; Lee, Kyu Young; Park, Arum; Seok, AeEun

2015-01-01

Objective Currently, there are a few biological markers to aid in the diagnosis and treatment of depression. However, it is not sufficient for diagnosis. We attempted to identify differentially expressed proteins during depressive moods as putative diagnostic biomarkers by using quantitative proteomic analysis of serum. Methods Blood samples were collected twice from five patients with major depressive disorder (MDD) at depressive status before treatment and at remission status during treatment. Samples were individually analyzed by liquid chromatography-tandem mass spectrometry for protein profiling. Differentially expressed proteins were analyzed by label-free quantification. Enzyme-linked immunosorbent assay (ELISA) results and receiver-operating characteristic (ROC) curves were used to validate the differentially expressed proteins. For validation, 8 patients with MDD including 3 additional patients and 8 matched normal controls were analyzed. Results The quantitative proteomic studies identified 10 proteins that were consistently upregulated or downregulated in 5 MDD patients. ELISA yielded results consistent with the proteomic analysis for 3 proteins. Expression levels were significantly different between normal controls and MDD patients. The 3 proteins were ceruloplasmin, inter-alpha-trypsin inhibitor heavy chain H4 and complement component 1qC, which were upregulated during the depressive status. The depressive status could be distinguished from the euthymic status from the ROC curves for these proteins, and this discrimination was enhanced when all 3 proteins were analyzed together. Conclusion This is the first proteomic study in MDD patients to compare intra-individual differences dependent on mood. This technique could be a useful approach to identify MDD biomarkers, but requires additional proteomic studies for validation. PMID:25866527

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.

Quantitative Metaproteomics and Activity-Based Probe Enrichment Reveals Significant Alterations in Protein Expression from a Mouse Model of Inflammatory Bowel Disease.

PubMed

Mayers, Michael D; Moon, Clara; Stupp, Gregory S; Su, Andrew I; Wolan, Dennis W

2017-02-03

Tandem mass spectrometry based shotgun proteomics of distal gut microbiomes is exceedingly difficult due to the inherent complexity and taxonomic diversity of the samples. We introduce two new methodologies to improve metaproteomic studies of microbiome samples. These methods include the stable isotope labeling in mammals to permit protein quantitation across two mouse cohorts as well as the application of activity-based probes to enrich and analyze both host and microbial proteins with specific functionalities. We used these technologies to study the microbiota from the adoptive T cell transfer mouse model of inflammatory bowel disease (IBD) and compare these samples to an isogenic control, thereby limiting genetic and environmental variables that influence microbiome composition. The data generated highlight quantitative alterations in both host and microbial proteins due to intestinal inflammation and corroborates the observed phylogenetic changes in bacteria that accompany IBD in humans and mouse models. The combination of isotope labeling with shotgun proteomics resulted in the total identification of 4434 protein clusters expressed in the microbial proteomic environment, 276 of which demonstrated differential abundance between control and IBD mice. Notably, application of a novel cysteine-reactive probe uncovered several microbial proteases and hydrolases overrepresented in the IBD mice. Implementation of these methods demonstrated that substantial insights into the identity and dysregulation of host and microbial proteins altered in IBD can be accomplished and can be used in the interrogation of other microbiome-related diseases.

Perturbations in the Urinary Exosome in Transplant Rejection

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

Sigdel, Tara K.; NG, Yolanda; Lee, Sangho

Background: Urine exosomes, vesicles exocytosed into urine by all renal epithelial cell types, occur under normal physiologic and disease states. Exosome contents may mirror disease-specific proteome perturbations in kidney injury. Analysis methodologies for the exosomal fraction of the urinary proteome were developed and for comparing the urinary exosomal fraction versus unfractionated proteome for biomarker discovery. Methods: Urine exosomes were isolated by centrifugal filtration from mid-stream, second morning void, urine samples collected from kidney transplant recipients with and without biopsy matched acute rejection. The proteomes of unfractionated whole urine (Uw) and urine exosomes (Uexo) underwent mass spectrometry-based quantitative proteomics analysis. Themore » proteome data were analyzed for significant differential protein abundances in acute rejection (AR). Results: Identifications of 1018 and 349 proteins, Uw and Uexo fractions, respectively, demonstrated a 279 protein overlap between the two urinary compartments with 25%(70) of overlapping proteins unique to Uexoand represented membrane bound proteins (p=9.31e-7). Of 349 urine exosomal proteins identified in transplant patients 220 were not previously identified in the normal urine exosomal fraction. Uexo proteins (11), functioning in the inflammatory / stress response, were more abundant in patients with biopsy-confirmed acute rejection, 3 of which were exclusive to Uexo. Uexo AR-specific biomarkers (8) were also detected in Uw, but since they were observed at significantly lower abundances in Uw, they were not significant for AR in Uw. Conclusions: A rapid urinary exosome isolation method and quantitative measurement of enriched Uexo proteins was applied. Urine proteins specific to the exosomal fraction were detected either in unfractionated urine (at low abundances) or by Uexo fraction analysis. Perturbed proteins in the exosomal compartment of urine collected from kidney transplant patients were specific to inflammatory responses, and were not observed in the Uexo fraction from normal healthy subjects. Uexo specific protein alterations in renal disease provide potential mechanistic insights and offer a unique panel of sensitive biomarkers for monitoring for acute transplant rejection.« less

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

Application of a label-free, gel-free quantitative proteomics method for ecotoxicological studies of small fish species

EPA Science Inventory

Although two-dimensional electrophoresis (2D-GE) remains the basis for many ecotoxicoproteomic analyses, new, non gel-based methods are beginning to be applied to overcome throughput and coverage limitations of 2D-GE. The overall objective of our research was to apply a comprehe...

Assay Portal | Office of Cancer Clinical Proteomics Research

Cancer.gov

The CPTAC Assay Portal serves as a centralized public repository of "fit-for-purpose," multiplexed quantitative mass spectrometry-based proteomic targeted assays. Targeted proteomic assays eliminate issues that are commonly observed using conventional protein detection systems.

Increased Depth and Breadth of Plasma Protein Quantitation via Two-Dimensional Liquid Chromatography/Multiple Reaction Monitoring-Mass Spectrometry with Labeled Peptide Standards.

PubMed

Percy, Andrew J; Yang, Juncong; Chambers, Andrew G; Borchers, Christoph H

2016-01-01

Absolute quantitative strategies are emerging as a powerful and preferable means of deriving concentrations in biological samples for systems biology applications. Method development is driven by the need to establish new-and validate current-protein biomarkers of high-to-low abundance for clinical utility. In this chapter, we describe a methodology involving two-dimensional (2D) reversed-phase liquid chromatography (RPLC), operated under alkaline and acidic pH conditions, combined with multiple reaction monitoring (MRM)-mass spectrometry (MS) (also called selected reaction monitoring (SRM)-MS) and a complex mixture of stable isotope-labeled standard (SIS) peptides, to quantify a broad and diverse panel of 253 proteins in human blood plasma. The quantitation range spans 8 orders of magnitude-from 15 mg/mL (for vitamin D-binding protein) to 450 pg/mL (for protein S100-B)-and includes 31 low-abundance proteins (defined as being <10 ng/mL) of potential disease relevance. The method is designed to assess candidates at the discovery and/or verification phases of the biomarker pipeline and can be adapted to examine smaller or alternate panels of proteins for higher sample throughput. Also detailed here is the application of our recently developed software tool-Qualis-SIS-for protein quantitation (via regression analysis of standard curves) and quality assessment of the resulting data. Overall, this chapter provides the blueprint for the replication of this quantitative proteomic method by proteomic scientists of all skill levels.

Quantitative proteomics in Giardia duodenalis-Achievements and challenges.

PubMed

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

2016-08-01

Giardia duodenalis (syn. G. lamblia and G. intestinalis) is a protozoan parasite of vertebrates and a major contributor to the global burden of diarrheal diseases and gastroenteritis. The publication of multiple genome sequences in the G. duodenalis species complex has provided important insights into parasite biology, and made post-genomic technologies, including proteomics, significantly more accessible. The aims of proteomics are to identify and quantify proteins present in a cell, and assign functions to them within the context of dynamic biological systems. In Giardia, proteomics in the post-genomic era has transitioned from reliance on gel-based systems to utilisation of a diverse array of techniques based on bottom-up LC-MS/MS technologies. Together, these have generated crucial foundations for subcellular proteomes, elucidated intra- and inter-assemblage isolate variation, and identified pathways and markers in differentiation, host-parasite interactions and drug resistance. However, in Giardia, proteomics remains an emerging field, with considerable shortcomings evident from the published research. These include a bias towards assemblage A, a lack of emphasis on quantitative analytical techniques, and limited information on post-translational protein modifications. Additionally, there are multiple areas of research for which proteomic data is not available to add value to published transcriptomic data. The challenge of amalgamating data in the systems biology paradigm necessitates the further generation of large, high-quality quantitative datasets to accurately model parasite biology. This review surveys the current proteomic research available for Giardia and evaluates their technical and quantitative approaches, while contextualising their biological insights into parasite pathology, isolate variation and eukaryotic evolution. Finally, we propose areas of priority for the generation of future proteomic data to explore fundamental questions in Giardia, including the analysis of post-translational modifications, and the design of MS-based assays for validation of differentially expressed proteins in large datasets. Copyright © 2016 Elsevier B.V. All rights reserved.

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

Cancer.gov

The National Cancer Institute (NCI), part of the National Institutes of Health, announces the launch of a Clinical Proteomic Tumor Analysis Consortium (CPTAC). CPTAC is a comprehensive, coordinated team effort to accelerate the understanding of the molecular basis of cancer through the application of robust, quantitative, proteomic technologies and workflows.

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

PubMed

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

2018-01-01

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

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

PubMed Central

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

2015-01-01

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

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

PubMed

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

2015-08-01

Democratization of genomics technologies has enabled the rapid determination of genotypes. More recently the democratization of comprehensive proteomics technologies is enabling the determination of the cellular phenotype and the molecular events that define its dynamic state. Core proteomic technologies include MS to define protein sequence, protein:protein interactions, and protein PTMs. Key enabling technologies for proteomics are bioinformatic pipelines to identify, quantitate, and summarize these events. The Trans-Proteomics Pipeline (TPP) is a robust open-source standardized data processing pipeline for large-scale reproducible quantitative MS proteomics. It supports all major operating systems and instrument vendors via open data formats. Here, we provide a review of the overall proteomics workflow supported by the TPP, its major tools, and how it can be used in its various modes from desktop to cloud computing. We describe new features for the TPP, including data visualization functionality. We conclude by describing some common perils that affect the analysis of MS/MS datasets, as well as some major upcoming features. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Quantitative proteomic analysis for high-throughput screening of differential glycoproteins in hepatocellular carcinoma serum

PubMed Central

Gao, Hua-Jun; Chen, Ya-Jing; Zuo, Duo; Xiao, Ming-Ming; Li, Ying; Guo, Hua; Zhang, Ning; Chen, Rui-Bing

2015-01-01

Objective Hepatocellular carcinoma (HCC) is a leading cause of cancer-related deaths. Novel serum biomarkers are required to increase the sensitivity and specificity of serum screening for early HCC diagnosis. This study employed a quantitative proteomic strategy to analyze the differential expression of serum glycoproteins between HCC and normal control serum samples. Methods Lectin affinity chromatography (LAC) was used to enrich glycoproteins from the serum samples. Quantitative mass spectrometric analysis combined with stable isotope dimethyl labeling and 2D liquid chromatography (LC) separations were performed to examine the differential levels of the detected proteins between HCC and control serum samples. Western blot was used to analyze the differential expression levels of the three serum proteins. Results A total of 2,280 protein groups were identified in the serum samples from HCC patients by using the 2D LC-MS/MS method. Up to 36 proteins were up-regulated in the HCC serum, whereas 19 proteins were down-regulated. Three differential glycoproteins, namely, fibrinogen gamma chain (FGG), FOS-like antigen 2 (FOSL2), and α-1,6-mannosylglycoprotein 6-β-N-acetylglucosaminyltransferase B (MGAT5B) were validated by Western blot. All these three proteins were up-regulated in the HCC serum samples. Conclusion A quantitative glycoproteomic method was established and proven useful to determine potential novel biomarkers for HCC. PMID:26487969

Label-free Quantitative Protein Profiling of vastus lateralis Muscle During Human Aging*

PubMed Central

Théron, Laëtitia; Gueugneau, Marine; Coudy, Cécile; Viala, Didier; Bijlsma, Astrid; Butler-Browne, Gillian; Maier, Andrea; Béchet, Daniel; Chambon, Christophe

2014-01-01

Sarcopenia corresponds to the loss of muscle mass occurring during aging, and is associated with a loss of muscle functionality. Proteomic links the muscle functional changes with protein expression pattern. To better understand the mechanisms involved in muscle aging, we performed a proteomic analysis of Vastus lateralis muscle in mature and older women. For this, a shotgun proteomic method was applied to identify soluble proteins in muscle, using a combination of high performance liquid chromatography and mass spectrometry. A label-free protein profiling was then conducted to quantify proteins and compare profiles from mature and older women. This analysis showed that 35 of the 366 identified proteins were linked to aging in muscle. Most of the proteins were under-represented in older compared with mature women. We built a functional interaction network linking the proteins differentially expressed between mature and older women. The results revealed that the main differences between mature and older women were defined by proteins involved in energy metabolism and proteins from the myofilament and cytoskeleton. This is the first time that label-free quantitative proteomics has been applied to study of aging mechanisms in human skeletal muscle. This approach highlights new elements for elucidating the alterations observed during aging and may lead to novel sarcopenia biomarkers. PMID:24217021

Label-free quantitative protein profiling of vastus lateralis muscle during human aging.

PubMed

Théron, Laëtitia; Gueugneau, Marine; Coudy, Cécile; Viala, Didier; Bijlsma, Astrid; Butler-Browne, Gillian; Maier, Andrea; Béchet, Daniel; Chambon, Christophe

2014-01-01

Sarcopenia corresponds to the loss of muscle mass occurring during aging, and is associated with a loss of muscle functionality. Proteomic links the muscle functional changes with protein expression pattern. To better understand the mechanisms involved in muscle aging, we performed a proteomic analysis of Vastus lateralis muscle in mature and older women. For this, a shotgun proteomic method was applied to identify soluble proteins in muscle, using a combination of high performance liquid chromatography and mass spectrometry. A label-free protein profiling was then conducted to quantify proteins and compare profiles from mature and older women. This analysis showed that 35 of the 366 identified proteins were linked to aging in muscle. Most of the proteins were under-represented in older compared with mature women. We built a functional interaction network linking the proteins differentially expressed between mature and older women. The results revealed that the main differences between mature and older women were defined by proteins involved in energy metabolism and proteins from the myofilament and cytoskeleton. This is the first time that label-free quantitative proteomics has been applied to study of aging mechanisms in human skeletal muscle. This approach highlights new elements for elucidating the alterations observed during aging and may lead to novel sarcopenia biomarkers.

From the genome sequence to the protein inventory of Bacillus subtilis.

PubMed

Becher, Dörte; Büttner, Knut; Moche, Martin; Hessling, Bernd; Hecker, Michael

2011-08-01

Owing to the low number of proteins necessary to render a bacterial cell viable, bacteria are extremely attractive model systems to understand how the genome sequence is translated into actual life processes. One of the most intensively investigated model organisms is Bacillus subtilis. It has attracted world-wide research interest, addressing cell differentiation and adaptation on a molecular scale as well as biotechnological production processes. Meanwhile, we are looking back on more than 25 years of B. subtilis proteomics. A wide range of methods have been developed during this period for the large-scale qualitative and quantitative proteome analysis. Currently, it is possible to identify and quantify more than 50% of the predicted proteome in different cellular subfractions. In this review, we summarize the development of B. subtilis proteomics during the past 25 years. Copyright © 2011 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

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

Final Report: Proteomic study of brassinosteroid responses in Arabidopsis

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

Wang, Zhiyong; Burlingame, Alma

2017-11-29

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

Efficient Exploitation of Separation Space in Two-Dimensional Liquid Chromatography System for Comprehensive and Efficient Proteomic Analyses.

PubMed

Lee, Hangyeore; Mun, Dong-Gi; So, Jeong Eun; Bae, Jingi; Kim, Hokeun; Masselon, Christophe; Lee, Sang-Won

2016-12-06

Proteomics aims to achieve complete profiling of the protein content and protein modifications in cells, tissues, and biofluids and to quantitatively determine changes in their abundances. This information serves to elucidate cellular processes and signaling pathways and to identify candidate protein biomarkers and/or therapeutic targets. Analyses must therefore be both comprehensive and efficient. Here, we present a novel online two-dimensional reverse-phase/reverse-phase liquid chromatography separation platform, which is based on a newly developed online noncontiguous fractionating and concatenating device (NCFC fractionator). In bottom-up proteomics analyses of a complex proteome, this system provided significantly improved exploitation of the separation space of the two RPs, considerably increasing the numbers of peptides identified compared to a contiguous 2D-RP/RPLC method. The fully automated online 2D-NCFC-RP/RPLC system bypassed a number of labor-intensive manual processes required with the previously described offline 2D-NCFC RP/RPLC method, and thus, it offers minimal sample loss in a context of highly reproducible 2D-RP/RPLC experiments.

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

PubMed

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

2013-01-01

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

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

PubMed Central

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

2013-01-01

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

A peptide-retrieval strategy enables significant improvement of quantitative performance without compromising confidence of identification.

PubMed

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

2017-01-30

Reliable quantification of low-abundance proteins in complex proteomes is challenging largely owing to the limited number of spectra/peptides identified. In this study we developed a straightforward method to improve the quantitative accuracy and precision of proteins by strategically retrieving the less confident peptides that were previously filtered out using the standard target-decoy search strategy. The filtered-out MS/MS spectra matched to confidently-identified proteins were recovered, and the peptide-spectrum-match FDR were re-calculated and controlled at a confident level of FDR≤1%, while protein FDR maintained at ~1%. We evaluated the performance of this strategy in both spectral count- and ion current-based methods. >60% increase of total quantified spectra/peptides was respectively achieved for analyzing a spike-in sample set and a public dataset from CPTAC. Incorporating the peptide retrieval strategy significantly improved the quantitative accuracy and precision, especially for low-abundance proteins (e.g. one-hit proteins). Moreover, the capacity of confidently discovering significantly-altered proteins was also enhanced substantially, as demonstrated with two spike-in datasets. In summary, improved quantitative performance was achieved by this peptide recovery strategy without compromising confidence of protein identification, which can be readily implemented in a broad range of quantitative proteomics techniques including label-free or labeling approaches. We hypothesize that more quantifiable spectra and peptides in a protein, even including less confident peptides, could help reduce variations and improve protein quantification. Hence the peptide retrieval strategy was developed and evaluated in two spike-in sample sets with different LC-MS/MS variations using both MS1- and MS2-based quantitative approach. The list of confidently identified proteins using the standard target-decoy search strategy was fixed and more spectra/peptides with less confidence matched to confident proteins were retrieved. However, the total peptide-spectrum-match false discovery rate (PSM FDR) after retrieval analysis was still controlled at a confident level of FDR≤1%. As expected, the penalty for occasionally incorporating incorrect peptide identifications is negligible by comparison with the improvements in quantitative performance. More quantifiable peptides, lower missing value rate, better quantitative accuracy and precision were significantly achieved for the same protein identifications by this simple strategy. This strategy is theoretically applicable for any quantitative approaches in proteomics and thereby provides more quantitative information, especially on low-abundance proteins. Published by Elsevier B.V.

Quantitative interaction proteomics using mass spectrometry.

PubMed

Wepf, Alexander; Glatter, Timo; Schmidt, Alexander; Aebersold, Ruedi; Gstaiger, Matthias

2009-03-01

We present a mass spectrometry-based strategy for the absolute quantification of protein complex components isolated through affinity purification. We quantified bait proteins via isotope-labeled reference peptides corresponding to an affinity tag sequence and prey proteins by label-free correlational quantification using the precursor ion signal intensities of proteotypic peptides generated in reciprocal purifications. We used this method to quantitatively analyze interaction stoichiometries in the human protein phosphatase 2A network.

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

PubMed Central

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

2009-01-01

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

Highly multiplexed and quantitative cell-surface protein profiling using genetically barcoded antibodies.

PubMed

Pollock, Samuel B; Hu, Amy; Mou, Yun; Martinko, Alexander J; Julien, Olivier; Hornsby, Michael; Ploder, Lynda; Adams, Jarrett J; Geng, Huimin; Müschen, Markus; Sidhu, Sachdev S; Moffat, Jason; Wells, James A

2018-03-13

Human cells express thousands of different surface proteins that can be used for cell classification, or to distinguish healthy and disease conditions. A method capable of profiling a substantial fraction of the surface proteome simultaneously and inexpensively would enable more accurate and complete classification of cell states. We present a highly multiplexed and quantitative surface proteomic method using genetically barcoded antibodies called phage-antibody next-generation sequencing (PhaNGS). Using 144 preselected antibodies displayed on filamentous phage (Fab-phage) against 44 receptor targets, we assess changes in B cell surface proteins after the development of drug resistance in a patient with acute lymphoblastic leukemia (ALL) and in adaptation to oncogene expression in a Myc-inducible Burkitt lymphoma model. We further show PhaNGS can be applied at the single-cell level. Our results reveal that a common set of proteins including FLT3, NCR3LG1, and ROR1 dominate the response to similar oncogenic perturbations in B cells. Linking high-affinity, selective, genetically encoded binders to NGS enables direct and highly multiplexed protein detection, comparable to RNA-sequencing for mRNA. PhaNGS has the potential to profile a substantial fraction of the surface proteome simultaneously and inexpensively to enable more accurate and complete classification of cell states. Copyright © 2018 the Author(s). Published by PNAS.

Integrated Proteomic Approaches for Understanding Toxicity of Environmental Chemicals

EPA Science Inventory

To apply quantitative proteomic analysis to the evaluation of toxicity of environmental chemicals, we have developed an integrated proteomic technology platform. This platform has been applied to the analysis of the toxic effects and pathways of many important environmental chemi...

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

PubMed

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

2017-08-01

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

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/.

A systematic evaluation of normalization methods in quantitative label-free proteomics.

PubMed

Välikangas, Tommi; Suomi, Tomi; Elo, Laura L

2018-01-01

To date, mass spectrometry (MS) data remain inherently biased as a result of reasons ranging from sample handling to differences caused by the instrumentation. Normalization is the process that aims to account for the bias and make samples more comparable. The selection of a proper normalization method is a pivotal task for the reliability of the downstream analysis and results. Many normalization methods commonly used in proteomics have been adapted from the DNA microarray techniques. Previous studies comparing normalization methods in proteomics have focused mainly on intragroup variation. In this study, several popular and widely used normalization methods representing different strategies in normalization are evaluated using three spike-in and one experimental mouse label-free proteomic data sets. The normalization methods are evaluated in terms of their ability to reduce variation between technical replicates, their effect on differential expression analysis and their effect on the estimation of logarithmic fold changes. Additionally, we examined whether normalizing the whole data globally or in segments for the differential expression analysis has an effect on the performance of the normalization methods. We found that variance stabilization normalization (Vsn) reduced variation the most between technical replicates in all examined data sets. Vsn also performed consistently well in the differential expression analysis. Linear regression normalization and local regression normalization performed also systematically well. Finally, we discuss the choice of a normalization method and some qualities of a suitable normalization method in the light of the results of our evaluation. © The Author 2016. Published by Oxford University Press.

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

PubMed Central

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

2015-01-01

Background Uveal melanoma is the most common malignancy of the adult eye. The overall mortality rate is high because this aggressive cancer often metastasizes before ophthalmic diagnosis. Quantitative proteomic analysis of primary metastasizing and non-metastasizing tumors was pursued for insights into mechanisms and biomarkers of uveal melanoma metastasis. Methods Eight metastatic and 7 non-metastatic human primary uveal melanoma tumors were analyzed by LC MS/MS iTRAQ technology with Bruch’s membrane/choroid complex from normal postmortem eyes as control tissue. Tryptic peptides from tumor and control proteins were labeled with iTRAQ tags, fractionated by cation exchange chromatography, and analyzed by LC MS/MS. Protein identification utilized the Mascot search engine and the human Uni-Prot/Swiss-Protein database with false discovery ≤ 1%; protein quantitation utilized the Mascot weighted average method. Proteins designated differentially expressed exhibited quantitative differences (p ≤ 0.05, t-test) in a training set of five metastatic and five non-metastatic tumors. Logistic regression models developed from the training set were used to classify the metastatic status of five independent tumors. Results Of 1644 proteins identified and quantified in 5 metastatic and 5 non-metastatic tumors, 12 proteins were found uniquely in ≥ 3 metastatic tumors, 28 were found significantly elevated and 30 significantly decreased only in metastatic tumors, and 31 were designated differentially expressed between metastatic and non-metastatic tumors. Logistic regression modeling of differentially expressed collagen alpha-3(VI) and heat shock protein beta-1 allowed correct prediction of metastasis status for each of five independent tumor specimens. Conclusions The present data provide new clues to molecular differences in metastatic and non-metastatic uveal melanoma tumors. While sample size is limited and validation required, the results support collagen alpha-3(VI) and heat shock protein beta-1 as candidate biomarkers of uveal melanoma metastasis and establish a quantitative proteomic database for uveal melanoma primary tumors. PMID:26305875

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

PubMed

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

2017-01-01

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

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

PubMed Central

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

2017-01-01

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

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

PubMed

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

2009-10-06

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

Global, quantitative and dynamic mapping of protein subcellular localization

PubMed Central

Itzhak, Daniel N; Tyanova, Stefka; Cox, Jürgen; Borner, Georg HH

2016-01-01

Subcellular localization critically influences protein function, and cells control protein localization to regulate biological processes. We have developed and applied Dynamic Organellar Maps, a proteomic method that allows global mapping of protein translocation events. We initially used maps statically to generate a database with localization and absolute copy number information for over 8700 proteins from HeLa cells, approaching comprehensive coverage. All major organelles were resolved, with exceptional prediction accuracy (estimated at >92%). Combining spatial and abundance information yielded an unprecedented quantitative view of HeLa cell anatomy and organellar composition, at the protein level. We subsequently demonstrated the dynamic capabilities of the approach by capturing translocation events following EGF stimulation, which we integrated into a quantitative model. Dynamic Organellar Maps enable the proteome-wide analysis of physiological protein movements, without requiring any reagents specific to the investigated process, and will thus be widely applicable in cell biology. DOI: http://dx.doi.org/10.7554/eLife.16950.001 PMID:27278775

Identification of Salmonella Typhimurium deubiquitinase SseL substrates by immunoaffinity enrichment and quantitative proteomic analysis

DOE PAGES

Nakayasu, Ernesto S.; Sydor, Michael A.; Brown, Roslyn N.; ...

2015-07-06

Ubiquitination is a key protein post-translational modification that regulates many important cellular pathways and whose levels are regulated by equilibrium between the activities of ubiquitin ligases and deubiquitinases. Here we present a method to identify specific deubiquitinase substrates based on treatment of cell lysates with recombinant enzymes, immunoaffinity purification and global quantitative proteomic analysis. As model system to identify substrates, we used a virulence-related deubiquitinase secreted by Salmonella enterica serovar Typhimurium into the host cells, SseL. By using this approach two SseL substrates were identified in RAW 264.7 murine macrophage-like cell line, S100A6 and het-erogeneous nuclear ribonuclear protein K, inmore » addition to the previously reported K63-linked ubiquitin chains. These substrates were further validated by a combination of enzymatic and binding assays. Finally, this method can be used for the systematic identification of substrates of deubiquitinases from other organisms and applied to study their functions in physiology and disease.« less

Identification of Salmonella Typhimurium deubiquitinase SseL substrates by immunoaffinity enrichment and quantitative proteomic analysis

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

Nakayasu, Ernesto S.; Sydor, Michael A.; Brown, Roslyn N.

Ubiquitination is a key protein post-translational modification that regulates many important cellular pathways and whose levels are regulated by equilibrium between the activities of ubiquitin ligases and deubiquitinases. Here we present a method to identify specific deubiquitinase substrates based on treatment of cell lysates with recombinant enzymes, immunoaffinity purification and global quantitative proteomic analysis. As model system to identify substrates, we used a virulence-related deubiquitinase secreted by Salmonella enterica serovar Typhimurium into the host cells, SseL. By using this approach two SseL substrates were identified in RAW 264.7 murine macrophage-like cell line, S100A6 and het-erogeneous nuclear ribonuclear protein K, inmore » addition to the previously reported K63-linked ubiquitin chains. These substrates were further validated by a combination of enzymatic and binding assays. Finally, this method can be used for the systematic identification of substrates of deubiquitinases from other organisms and applied to study their functions in physiology and disease.« less

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.

Quantitative Proteomics via High Resolution MS Quantification: Capabilities and Limitations

PubMed Central

Higgs, Richard E.; Butler, Jon P.; Han, Bomie; Knierman, Michael D.

2013-01-01

Recent improvements in the mass accuracy and resolution of mass spectrometers have led to renewed interest in label-free quantification using data from the primary mass spectrum (MS1) acquired from data-dependent proteomics experiments. The capacity for higher specificity quantification of peptides from samples enriched for proteins of biological interest offers distinct advantages for hypothesis generating experiments relative to immunoassay detection methods or prespecified peptide ions measured by multiple reaction monitoring (MRM) approaches. Here we describe an evaluation of different methods to post-process peptide level quantification information to support protein level inference. We characterize the methods by examining their ability to recover a known dilution of a standard protein in background matrices of varying complexity. Additionally, the MS1 quantification results are compared to a standard, targeted, MRM approach on the same samples under equivalent instrument conditions. We show the existence of multiple peptides with MS1 quantification sensitivity similar to the best MRM peptides for each of the background matrices studied. Based on these results we provide recommendations on preferred approaches to leveraging quantitative measurements of multiple peptides to improve protein level inference. PMID:23710359

DAnTE: a statistical tool for quantitative analysis of –omics data

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

Polpitiya, Ashoka D.; Qian, Weijun; Jaitly, Navdeep

2008-05-03

DAnTE (Data Analysis Tool Extension) is a statistical tool designed to address challenges unique to quantitative bottom-up, shotgun proteomics data. This tool has also been demonstrated for microarray data and can easily be extended to other high-throughput data types. DAnTE features selected normalization methods, missing value imputation algorithms, peptide to protein rollup methods, an extensive array of plotting functions, and a comprehensive ANOVA scheme that can handle unbalanced data and random effects. The Graphical User Interface (GUI) is designed to be very intuitive and user friendly.

Magnetoresistive biosensors for quantitative proteomics

NASA Astrophysics Data System (ADS)

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

2017-08-01

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

Detergents: Friends not foes for high-performance membrane proteomics toward precision medicine.

PubMed

Zhang, Xi

2017-02-01

Precision medicine, particularly therapeutics, emphasizes the atomic-precise, dynamic, and systems visualization of human membrane proteins and their endogenous modifiers. For years, bottom-up proteomics has grappled with removing and avoiding detergents, yet faltered at the therapeutic-pivotal membrane proteins, which have been tackled by classical approaches and are known for decades refractory to single-phase aqueous or organic denaturants. Hydrophobicity and aggregation commonly challenge tissue and cell lysates, biofluids, and enriched samples. Frequently, expected membrane proteins and peptides are not identified by shotgun bottom-up proteomics, let alone robust quantitation. This review argues the cause of this proteomic crisis is not detergents per se, but the choice of detergents. Recently, inclusion of compatible detergents for membrane protein extraction and digestion has revealed stark improvements in both quantitative and structural proteomics. This review analyzes detergent properties behind recent proteomic advances, and proposes that rational use of detergents may reconcile outstanding membrane proteomics dilemmas, enabling ultradeep coverage and minimal artifacts for robust protein and endogenous PTM measurements. The simplicity of detergent tools confers bottom-up membrane proteomics the sophistication toward precision medicine. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Proteomic Approach for Extracting Cytoplasmic Proteins from Streptococcus sanguinis using Mass Spectrometry

PubMed Central

El-Rami, Fadi; Nelson, Kristina; Xu, Ping

2017-01-01

Streptococcus sanguinis is a commensal and early colonizer of oral cavity as well as an opportunistic pathogen of infectious endocarditis. Extracting the soluble proteome of this bacterium provides deep insights about the physiological dynamic changes under different growth and stress conditions, thus defining “proteomic signatures” as targets for therapeutic intervention. In this protocol, we describe an experimentally verified approach to extract maximal cytoplasmic proteins from Streptococcus sanguinis SK36 strain. A combination of procedures was adopted that broke the thick cell wall barrier and minimized denaturation of the intracellular proteome, using optimized buffers and a sonication step. Extracted proteome was quantitated using Pierce BCA Protein Quantitation assay and protein bands were macroscopically assessed by Coomassie Blue staining. Finally, a high resolution detection of the extracted proteins was conducted through Synapt G2Si mass spectrometer, followed by label-free relative quantification via Progenesis QI. In conclusion, this pipeline for proteomic extraction and analysis of soluble proteins provides a fundamental tool in deciphering the biological complexity of Streptococcus sanguinis. PMID:29152022

Simple preparation of plant epidermal tissue for laser microdissection and downstream quantitative proteome and carbohydrate analysis

PubMed Central

Falter, Christian; Ellinger, Dorothea; von Hülsen, Behrend; Heim, René; Voigt, Christian A.

2015-01-01

The outwardly directed cell wall and associated plasma membrane of epidermal cells represent the first layers of plant defense against intruding pathogens. Cell wall modifications and the formation of defense structures at sites of attempted pathogen penetration are decisive for plant defense. A precise isolation of these stress-induced structures would allow a specific analysis of regulatory mechanism and cell wall adaption. However, methods for large-scale epidermal tissue preparation from the model plant Arabidopsis thaliana, which would allow proteome and cell wall analysis of complete, laser-microdissected epidermal defense structures, have not been provided. We developed the adhesive tape – liquid cover glass technique (ACT) for simple leaf epidermis preparation from A. thaliana, which is also applicable on grass leaves. This method is compatible with subsequent staining techniques to visualize stress-related cell wall structures, which were precisely isolated from the epidermal tissue layer by laser microdissection (LM) coupled to laser pressure catapulting. We successfully demonstrated that these specific epidermal tissue samples could be used for quantitative downstream proteome and cell wall analysis. The development of the ACT for simple leaf epidermis preparation and the compatibility to LM and downstream quantitative analysis opens new possibilities in the precise examination of stress- and pathogen-related cell wall structures in epidermal cells. Because the developed tissue processing is also applicable on A. thaliana, well-established, model pathosystems that include the interaction with powdery mildews can be studied to determine principal regulatory mechanisms in plant–microbe interaction with their potential outreach into crop breeding. PMID:25870605

Simple preparation of plant epidermal tissue for laser microdissection and downstream quantitative proteome and carbohydrate analysis.

PubMed

Falter, Christian; Ellinger, Dorothea; von Hülsen, Behrend; Heim, René; Voigt, Christian A

2015-01-01

The outwardly directed cell wall and associated plasma membrane of epidermal cells represent the first layers of plant defense against intruding pathogens. Cell wall modifications and the formation of defense structures at sites of attempted pathogen penetration are decisive for plant defense. A precise isolation of these stress-induced structures would allow a specific analysis of regulatory mechanism and cell wall adaption. However, methods for large-scale epidermal tissue preparation from the model plant Arabidopsis thaliana, which would allow proteome and cell wall analysis of complete, laser-microdissected epidermal defense structures, have not been provided. We developed the adhesive tape - liquid cover glass technique (ACT) for simple leaf epidermis preparation from A. thaliana, which is also applicable on grass leaves. This method is compatible with subsequent staining techniques to visualize stress-related cell wall structures, which were precisely isolated from the epidermal tissue layer by laser microdissection (LM) coupled to laser pressure catapulting. We successfully demonstrated that these specific epidermal tissue samples could be used for quantitative downstream proteome and cell wall analysis. The development of the ACT for simple leaf epidermis preparation and the compatibility to LM and downstream quantitative analysis opens new possibilities in the precise examination of stress- and pathogen-related cell wall structures in epidermal cells. Because the developed tissue processing is also applicable on A. thaliana, well-established, model pathosystems that include the interaction with powdery mildews can be studied to determine principal regulatory mechanisms in plant-microbe interaction with their potential outreach into crop breeding.

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

PubMed

Du, Chao; van Wezel, Gilles P

2018-04-30

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

Human borna disease virus infection impacts host proteome and histone lysine acetylation in human oligodendroglia cells

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

Liu, Xia; Department of Neurology, The Fifth People's Hospital of Shanghai, School of Medicine, Fudan University, Shanghai, 200240; Zhao, Libo

2014-09-15

Background: Borna disease virus (BDV) replicates in the nucleus and establishes persistent infections in mammalian hosts. A human BDV strain was used to address the first time, how BDV infection impacts the proteome and histone lysine acetylation (Kac) of human oligodendroglial (OL) cells, thus allowing a better understanding of infection-driven pathophysiology in vitro. Methods: Proteome and histone lysine acetylation were profiled through stable isotope labeling for cell culture (SILAC)-based quantitative proteomics. The quantifiable proteome was annotated using bioinformatics. Histone acetylation changes were validated by biochemistry assays. Results: Post BDV infection, 4383 quantifiable differential proteins were identified and functionally annotated tomore » metabolism pathways, immune response, DNA replication, DNA repair, and transcriptional regulation. Sixteen of the thirty identified Kac sites in core histones presented altered acetylation levels post infection. Conclusions: BDV infection using a human strain impacted the whole proteome and histone lysine acetylation in OL cells. - Highlights: • A human strain of BDV (BDV Hu-H1) was used to infect human oligodendroglial cells (OL cells). • This study is the first to reveal the host proteomic and histone Kac profiles in BDV-infected OL cells. • BDV infection affected the expression of many transcription factors and several HATs and HDACs.« 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.

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

EPA Science Inventory

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

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.

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

PubMed Central

Gunawardena, Harsha P.; Feltcher, Meghan E.; Wrobel, John A.; Gu, Sheng; Braunstein, Miriam; Chen, Xian

2015-01-01

The Mycobacterium tuberculosis (MTB) membrane is rich in antigens that are potential targets for diagnostics and the development of new vaccines. To better understand the mechanisms underlying MTB virulence and identify new targets for therapeutic intervention we investigated the differential composition of membrane proteomes between virulent M. tuberculosis H37Rv (MTB) and the Mycobacterium bovis BCG vaccine strain. To compare the membrane proteomes, we used LC-MS/MS analysis in combination with label-free quantitative (LFQ) proteomics, utilizing the area-under-curve (AUC) of the extracted ion chromatograms (XIC) of peptides obtained from m/z and retention time alignment of MS1 features. With this approach, we obtained relative abundance ratios for 2,203 identified membrane-associated proteins in high confidence. Of these proteins, 294 showed statistically significant differences of at least 2 fold, in relative abundance between MTB and BCG membrane fractions. Our comparative analysis detected several proteins associated with known genomic regions of difference between MTB and BCG as being absent, which validated the accuracy of our approach. In further support of our label-free quantitative data, we verified select protein differences by immunoblotting. To our knowledge we have generated the first comprehensive and high coverage profile of comparative membrane proteome changes between virulent MTB and its attenuated relative BCG, which helps elucidate the proteomic basis of the intrinsic virulence of the MTB pathogen. PMID:24093440

Proteomic analysis of Medulloblastoma reveals functional biology with translational potential.

PubMed

Rivero-Hinojosa, Samuel; Lau, Ling San; Stampar, Mojca; Staal, Jerome; Zhang, Huizhen; Gordish-Dressman, Heather; Northcott, Paul A; Pfister, Stefan M; Taylor, Michael D; Brown, Kristy J; Rood, Brian R

2018-06-07

Genomic characterization has begun to redefine diagnostic classifications of cancers. However, it remains a challenge to infer disease phenotypes from genomic alterations alone. To help realize the promise of genomics, we have performed a quantitative proteomics investigation using Stable Isotope Labeling by Amino Acids in Cell Culture (SILAC) and 41 tissue samples spanning the 4 genomically based subgroups of medulloblastoma and control cerebellum. We have identified and quantitated thousands of proteins across these groups and find that we are able to recapitulate the genomic subgroups based upon subgroup restricted and differentially abundant proteins while also identifying subgroup specific protein isoforms. Integrating our proteomic measurements with genomic data, we calculate a poor correlation between mRNA and protein abundance. Using EPIC 850 k methylation array data on the same tissues, we also investigate the influence of copy number alterations and DNA methylation on the proteome in an attempt to characterize the impact of these genetic features on the proteome. Reciprocally, we are able to use the proteome to identify which genomic alterations result in altered protein abundance and thus are most likely to impact biology. Finally, we are able to assemble protein-based pathways yielding potential avenues for clinical intervention. From these, we validate the EIF4F cap-dependent translation pathway as a novel druggable pathway in medulloblastoma. Thus, quantitative proteomics complements genomic platforms to yield a more complete understanding of functional tumor biology and identify novel therapeutic targets for medulloblastoma.

Missing Value Monitoring Enhances the Robustness in Proteomics Quantitation.

PubMed

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

2017-04-07

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

QuantFusion: Novel Unified Methodology for Enhanced Coverage and Precision in Quantifying Global Proteomic Changes in Whole Tissues.

PubMed

Gunawardena, Harsha P; O'Brien, Jonathon; Wrobel, John A; Xie, Ling; Davies, Sherri R; Li, Shunqiang; Ellis, Matthew J; Qaqish, Bahjat F; Chen, Xian

2016-02-01

Single quantitative platforms such as label-based or label-free quantitation (LFQ) present compromises in accuracy, precision, protein sequence coverage, and speed of quantifiable proteomic measurements. To maximize the quantitative precision and the number of quantifiable proteins or the quantifiable coverage of tissue proteomes, we have developed a unified approach, termed QuantFusion, that combines the quantitative ratios of all peptides measured by both LFQ and label-based methodologies. Here, we demonstrate the use of QuantFusion in determining the proteins differentially expressed in a pair of patient-derived tumor xenografts (PDXs) representing two major breast cancer (BC) subtypes, basal and luminal. Label-based in-spectra quantitative peptides derived from amino acid-coded tagging (AACT, also known as SILAC) of a non-malignant mammary cell line were uniformly added to each xenograft with a constant predefined ratio, from which Ratio-of-Ratio estimates were obtained for the label-free peptides paired with AACT peptides in each PDX tumor. A mixed model statistical analysis was used to determine global differential protein expression by combining complementary quantifiable peptide ratios measured by LFQ and Ratio-of-Ratios, respectively. With minimum number of replicates required for obtaining the statistically significant ratios, QuantFusion uses the distinct mechanisms to "rescue" the missing data inherent to both LFQ and label-based quantitation. Combined quantifiable peptide data from both quantitative schemes increased the overall number of peptide level measurements and protein level estimates. In our analysis of the PDX tumor proteomes, QuantFusion increased the number of distinct peptide ratios by 65%, representing differentially expressed proteins between the BC subtypes. This quantifiable coverage improvement, in turn, not only increased the number of measurable protein fold-changes by 8% but also increased the average precision of quantitative estimates by 181% so that some BC subtypically expressed proteins were rescued by QuantFusion. Thus, incorporating data from multiple quantitative approaches while accounting for measurement variability at both the peptide and global protein levels make QuantFusion unique for obtaining increased coverage and quantitative precision for tissue proteomes. © 2016 by The American Society for Biochemistry and Molecular Biology, Inc.

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

PubMed

Bilić, Petra; Guillemin, Nicolas; Kovačević, Alan; Beer Ljubić, Blanka; Jović, Ines; Galan, Asier; Eckersall, Peter David; Burchmore, Richard; Mrljak, Vladimir

2018-05-15

Idiopathic dilated cardiomyopathy (iDCM) is a primary myocardial disorder with an unknown aetiology, characterized by reduced contractility and ventricular dilation of the left or both ventricles. Naturally occurring canine iDCM was used herein to identify serum proteomic signature of the disease compared to the healthy state, providing an insight into underlying mechanisms and revealing proteins with biomarker potential. To achieve this, we used high-throughput label-based quantitative LC-MS/MS proteomics approach and bioinformatics analysis of the in silico inferred interactome protein network created from the initial list of differential proteins. To complement the proteomic analysis, serum biochemical parameters and levels of know biomarkers of cardiac function were measured. Several proteins with biomarker potential were identified, such as inter-alpha-trypsin inhibitor heavy chain H4, microfibril-associated glycoprotein 4 and apolipoprotein A-IV, which were validated using an independent method (Western blotting) and showed high specificity and sensitivity according to the receiver operating characteristic curve analysis. Bioinformatics analysis revealed involvement of different pathways in iDCM, such as complement cascade activation, lipoprotein particles dynamics, elastic fibre formation, GPCR signalling and respiratory electron transport chain. Idiopathic dilated cardiomyopathy is a severe primary myocardial disease of unknown cause, affecting both humans and dogs. This study is a contribution to the canine heart disease research by means of proteomic and bioinformatic state of the art analyses, following similar approach in human iDCM research. Importantly, we used serum as non-invasive and easily accessible biological source of information and contributed to the scarce data on biofluid proteome research on this topic. Bioinformatics analysis revealed biological pathways modulated in canine iDCM with potential of further targeted research. Also, several proteins with biomarker potential have been identified and successfully validated. Copyright © 2018 Elsevier B.V. All rights reserved.

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.

Quantitative Method to Investigate the Balance between Metabolism and Proteome Biomass: Starting from Glycine.

PubMed

Gu, Haiwei; Carroll, Patrick A; Du, Jianhai; Zhu, Jiangjiang; Neto, Fausto Carnevale; Eisenman, Robert N; Raftery, Daniel

2016-12-12

The balance between metabolism and biomass is very important in biological systems; however, to date there has been no quantitative method to characterize the balance. In this methodological study, we propose to use the distribution of amino acids in different domains to investigate this balance. It is well known that endogenous or exogenous amino acids in a biological system are either metabolized or incorporated into free amino acids (FAAs) or proteome amino acids (PAAs). Using glycine (Gly) as an example, we demonstrate a novel method to accurately determine the amounts of amino acids in various domains using serum, urine, and cell samples. As expected, serum and urine had very different distributions of FAA- and PAA-Gly. Using Tet21N human neuroblastoma cells, we also found that Myc(oncogene)-induced metabolic reprogramming included a higher rate of metabolizing Gly, which provides additional evidence that the metabolism of proliferating cells is adapted to facilitate producing new cells. It is therefore anticipated that our method will be very valuable for further studies of the metabolism and biomass balance that will lead to a better understanding of human cancers. © 2016 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

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

PubMed

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

2016-10-28

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

Automation of dimethylation after guanidination labeling chemistry and its compatibility with common buffers and surfactants for mass spectrometry-based shotgun quantitative proteome analysis.

PubMed

Lo, Andy; Tang, Yanan; Chen, Lu; Li, Liang

2013-07-25

Isotope labeling liquid chromatography-mass spectrometry (LC-MS) is a major analytical platform for quantitative proteome analysis. Incorporation of isotopes used to distinguish samples plays a critical role in the success of this strategy. In this work, we optimized and automated a chemical derivatization protocol (dimethylation after guanidination, 2MEGA) to increase the labeling reproducibility and reduce human intervention. We also evaluated the reagent compatibility of this protocol to handle biological samples in different types of buffers and surfactants. A commercially available liquid handler was used for reagent dispensation to minimize analyst intervention and at least twenty protein digest samples could be prepared in a single run. Different front-end sample preparation methods for protein solubilization (SDS, urea, Rapigest™, and ProteaseMAX™) and two commercially available cell lysis buffers were evaluated for compatibility with the automated protocol. It was found that better than 94% desired labeling could be obtained in all conditions studied except urea, where the rate was reduced to about 92% due to carbamylation on the peptide amines. This work illustrates the automated 2MEGA labeling process can be used to handle a wide range of protein samples containing various reagents that are often encountered in protein sample preparation for quantitative proteome analysis. Copyright © 2013 Elsevier B.V. All rights reserved.

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

PubMed

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

2009-06-01

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

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

PubMed

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

2011-01-01

Image data are increasingly encountered and are of growing importance in many areas of science. Much of these data are quantitative image data, which are characterized by intensities that represent some measurement of interest in the scanned images. The data typically consist of multiple images on the same domain and the goal of the research is to combine the quantitative information across images to make inference about populations or interventions. In this paper, we present a unified analysis framework for the analysis of quantitative image data using a Bayesian functional mixed model approach. This framework is flexible enough to handle complex, irregular images with many local features, and can model the simultaneous effects of multiple factors on the image intensities and account for the correlation between images induced by the design. We introduce a general isomorphic modeling approach to fitting the functional mixed model, of which the wavelet-based functional mixed model is one special case. With suitable modeling choices, this approach leads to efficient calculations and can result in flexible modeling and adaptive smoothing of the salient features in the data. The proposed method has the following advantages: it can be run automatically, it produces inferential plots indicating which regions of the image are associated with each factor, it simultaneously considers the practical and statistical significance of findings, and it controls the false discovery rate. Although the method we present is general and can be applied to quantitative image data from any application, in this paper we focus on image-based proteomic data. We apply our method to an animal study investigating the effects of opiate addiction on the brain proteome. Our image-based functional mixed model approach finds results that are missed with conventional spot-based analysis approaches. In particular, we find that the significant regions of the image identified by the proposed method frequently correspond to subregions of visible spots that may represent post-translational modifications or co-migrating proteins that cannot be visually resolved from adjacent, more abundant proteins on the gel image. Thus, it is possible that this image-based approach may actually improve the realized resolution of the gel, revealing differentially expressed proteins that would not have even been detected as spots by modern spot-based analyses.

High-resolution proteomic profiling of spider venom: expanding the toxin diversity of Phoneutria nigriventer venom.

PubMed

Liberato, Tarcísio; Troncone, Lanfranco Ranieri Paolo; Yamashiro, Edson T; Serrano, Solange M T; Zelanis, André

2016-03-01

Here we present a proteomic characterization of Phoneutria nigriventer venom. A shotgun proteomic approach allowed the identification, for the first time, of O-glycosyl hydrolases (chitinases) in P. nigriventer venom. The electrophoretic profiles under nonreducing and reducing conditions, and protein identification by mass spectrometry, indicated the presence of oligomeric toxin structures in the venom. Complementary proteomic approaches allowed for a qualitative and semi-quantitative profiling of P. nigriventer venom complexity, expanding its known venom proteome diversity.

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

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.

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

PubMed Central

Kuzniar, Arnold; Kanaar, Roland

2014-01-01

We present the Proteomics Identifications and Quantitations Data Management and Integration Service or PIQMIe that aids in reliable and scalable data management, analysis and visualization of semi-quantitative mass spectrometry based proteomics experiments. PIQMIe readily integrates peptide and (non-redundant) protein identifications and quantitations from multiple experiments with additional biological information on the protein entries, and makes the linked data available in the form of a light-weight relational database, which enables dedicated data analyses (e.g. in R) and user-driven queries. Using the web interface, users are presented with a concise summary of their proteomics experiments in numerical and graphical forms, as well as with a searchable protein grid and interactive visualization tools to aid in the rapid assessment of the experiments and in the identification of proteins of interest. The web server not only provides data access through a web interface but also supports programmatic access through RESTful web service. The web server is available at http://piqmie.semiqprot-emc.cloudlet.sara.nl or http://www.bioinformatics.nl/piqmie. This website is free and open to all users and there is no login requirement. PMID:24861615

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

PubMed

Kuzniar, Arnold; Kanaar, Roland

2014-07-01

We present the Proteomics Identifications and Quantitations Data Management and Integration Service or PIQMIe that aids in reliable and scalable data management, analysis and visualization of semi-quantitative mass spectrometry based proteomics experiments. PIQMIe readily integrates peptide and (non-redundant) protein identifications and quantitations from multiple experiments with additional biological information on the protein entries, and makes the linked data available in the form of a light-weight relational database, which enables dedicated data analyses (e.g. in R) and user-driven queries. Using the web interface, users are presented with a concise summary of their proteomics experiments in numerical and graphical forms, as well as with a searchable protein grid and interactive visualization tools to aid in the rapid assessment of the experiments and in the identification of proteins of interest. The web server not only provides data access through a web interface but also supports programmatic access through RESTful web service. The web server is available at http://piqmie.semiqprot-emc.cloudlet.sara.nl or http://www.bioinformatics.nl/piqmie. This website is free and open to all users and there is no login requirement. © The Author(s) 2014. Published by Oxford University Press on behalf of Nucleic Acids Research.

Comparative study of label and label-free techniques using shotgun proteomics for relative protein quantification.

PubMed

Sjödin, Marcus O D; Wetterhall, Magnus; Kultima, Kim; Artemenko, Konstantin

2013-06-01

The analytical performance of three different strategies, iTRAQ (isobaric tag for relative and absolute quantification), dimethyl labeling (DML) and label free (LF) for relative protein quantification using shotgun proteomics have been evaluated. The methods have been explored using samples containing (i) Bovine proteins in known ratios and (ii) Bovine proteins in known ratios spiked into Escherichia coli. The latter case mimics the actual conditions in a typical biological sample with a few differentially expressed proteins and a bulk of proteins with unchanged ratios. Additionally, the evaluation was performed on both QStar and LTQ-FTICR mass spectrometers. LF LTQ-FTICR was found to have the highest proteome coverage while the highest accuracy based on the artificially regulated proteins was found for DML LTQ-FTICR (54%). A varying linearity (k: 0.55-1.16, r(2): 0.61-0.96) was shown for all methods within selected dynamic ranges. All methods were found to consistently underestimate Bovine protein ratios when matrix proteins were added. However, LF LTQ-FTICR was more tolerant toward a compression effect. A single peptide was demonstrated to be sufficient for a reliable quantification using iTRAQ. A ranking system utilizing several parameters important for quantitative proteomics demonstrated that the overall performance of the five different methods was; DML LTQ-FTICR>iTRAQ QStar>LF LTQ-FTICR>DML QStar>LF QStar. Copyright © 2013 Elsevier B.V. All rights reserved.

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

PubMed

Lo, Andy; Weiner, Joel H; Li, Liang

2013-09-17

Due to limited sample amounts, instrument time considerations, and reagent costs, only a small number of replicate experiments are typically performed for quantitative proteome analyses. Generation of reproducible data that can be readily assessed for consistency within a small number of datasets is critical for accurate quantification. We report our investigation of a strategy using reciprocal isotope labeling of two comparative samples as a tool for determining proteome changes. Reciprocal labeling was evaluated to determine the internal consistency of quantified proteome changes from Escherichia coli grown under aerobic and anaerobic conditions. Qualitatively, the peptide overlap between replicate analyses of the same sample and reverse labeled samples were found to be within 8%. Quantitatively, reciprocal analyses showed only a slight increase in average overall inconsistency when compared with replicate analyses (1.29 vs. 1.24-fold difference). Most importantly, reverse labeling was successfully used to identify spurious values resulting from incorrect peptide identifications and poor peak fitting. After removal of 5% of the peptide data with low reproducibility, a total of 275 differentially expressed proteins (>1.50-fold difference) were consistently identified and were then subjected to bioinformatics analysis. General considerations and guidelines for reciprocal labeling experimental design and biological significance of obtained results are discussed. Copyright © 2013 Elsevier B.V. All rights reserved.

Proteomics Analysis of the Nucleolus in Adenovirus-infected Cells

PubMed Central

Lam, Yun W.; Evans, Vanessa C.; Heesom, Kate J.; Lamond, Angus I.; Matthews, David A.

2010-01-01

Adenoviruses replicate primarily in the host cell nucleus, and it is well established that adenovirus infection affects the structure and function of host cell nucleoli in addition to coding for a number of nucleolar targeted viral proteins. Here we used unbiased proteomics methods, including high throughput mass spectrometry coupled with stable isotope labeling by amino acids in cell culture (SILAC) and traditional two-dimensional gel electrophoresis, to identify quantitative changes in the protein composition of the nucleolus during adenovirus infection. Two-dimensional gel analysis revealed changes in six proteins. By contrast, SILAC-based approaches identified 351 proteins with 24 proteins showing at least a 2-fold change after infection. Of those, four were previously reported to have aberrant localization and/or functional relevance during adenovirus infection. In total, 15 proteins identified as changing in amount by proteomics methods were examined in infected cells using confocal microscopy. Eleven of these proteins showed altered patterns of localization in adenovirus-infected cells. Comparing our data with the effects of actinomycin D on the nucleolar proteome revealed that adenovirus infection apparently specifically targets a relatively small subset of nucleolar antigens at the time point examined. PMID:19812395

Proteomics analysis of the nucleolus in adenovirus-infected cells.

PubMed

Lam, Yun W; Evans, Vanessa C; Heesom, Kate J; Lamond, Angus I; Matthews, David A

2010-01-01

Adenoviruses replicate primarily in the host cell nucleus, and it is well established that adenovirus infection affects the structure and function of host cell nucleoli in addition to coding for a number of nucleolar targeted viral proteins. Here we used unbiased proteomics methods, including high throughput mass spectrometry coupled with stable isotope labeling by amino acids in cell culture (SILAC) and traditional two-dimensional gel electrophoresis, to identify quantitative changes in the protein composition of the nucleolus during adenovirus infection. Two-dimensional gel analysis revealed changes in six proteins. By contrast, SILAC-based approaches identified 351 proteins with 24 proteins showing at least a 2-fold change after infection. Of those, four were previously reported to have aberrant localization and/or functional relevance during adenovirus infection. In total, 15 proteins identified as changing in amount by proteomics methods were examined in infected cells using confocal microscopy. Eleven of these proteins showed altered patterns of localization in adenovirus-infected cells. Comparing our data with the effects of actinomycin D on the nucleolar proteome revealed that adenovirus infection apparently specifically targets a relatively small subset of nucleolar antigens at the time point examined.

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

PubMed

Tiberti, Natalia; Sanchez, Jean-Charles

2015-09-01

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

Proteomics in bone research

PubMed Central

Zhang, Hengwei; Recker, Robert; Lee, Wai-Nang Paul; Xiao, Gary Guishan

2010-01-01

Osteoporosis is prevalent among the elderly and is a major cause of bone fracture in this population. Bone integrity is maintained by the dynamic processes of bone resorption and bone formation (bone remodeling). Osteoporosis results when there is an imbalance of the two counteracting processes. Bone mineral density, measured by dual-energy x-ray absorptiometry has been the primary method to assess fracture risk for decades. Recent studies demonstrated that measurement of bone turnover markers allows for a dynamic assessment of bone remodeling, while imaging techniques, such as dual-energy x-ray absorptiometry, do not. The application of proteomics has permitted discoveries of new, sensitive, bone turnover markers, which provide unique information for clinical diagnosis and treatment of patients with bone diseases. This review summarizes the recent findings of proteomic studies on bone diseases, properties of mesenchymal stem cells with high expansion rates and osteoblast and osteoclast differentiation, with emphasis on the role of quantitative proteomics in the study of signaling dynamics, biomarkers and discovery of therapeutic targets. PMID:20121480

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).

2D-DIGE in Proteomics.

PubMed

Pasquali, Matias; Serchi, Tommaso; Planchon, Sebastien; Renaut, Jenny

2017-01-01

The two-dimensional difference gel electrophoresis method is a valuable approach for proteomics. The method, using cyanine fluorescent dyes, allows the co-migration of multiple protein samples in the same gel and their simultaneous detection, thus reducing experimental and analytical time. 2D-DIGE, compared to traditional post-staining 2D-PAGE protocols (e.g., colloidal Coomassie or silver nitrate), provides faster and more reliable gel matching, limiting the impact of gel to gel variation, and allows also a good dynamic range for quantitative comparisons. By the use of internal standards, it is possible to normalize for experimental variations in spot intensities and gel patterns. Here we describe the experimental steps we follow in our routine 2D-DIGE procedure that we then apply to multiple biological questions.

Quantitative proteomics of bronchoalveolar lavage fluid in lung adenocarcinoma.

PubMed

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

2015-01-01

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

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/.

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

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

PubMed Central

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

2016-01-01

Black pepper (Piper nigrum L.), a tropical spice crop of global acclaim, is susceptible to Phytophthora capsici, an oomycete pathogen which causes the highly destructive foot rot disease. A systematic understanding of this phytopathosystem has not been possible owing to lack of genome or proteome information. In this study, we explain an integrated transcriptome-assisted label-free quantitative proteomics pipeline to study the basal immune components of black pepper when challenged with P. capsici. We report a global identification of 532 novel leaf proteins from black pepper, of which 518 proteins were functionally annotated using BLAST2GO tool. A label-free quantitation of the protein datasets revealed 194 proteins common to diseased and control protein datasets of which 22 proteins showed significant up-regulation and 134 showed significant down-regulation. Ninety-three proteins were identified exclusively on P. capsici infected leaf tissues and 245 were expressed only in mock (control) infected samples. In-depth analysis of our data gives novel insights into the regulatory pathways of black pepper which are compromised during the infection. Differential down-regulation was observed in a number of critical pathways like carbon fixation in photosynthetic organism, cyano-amino acid metabolism, fructose, and mannose metabolism, glutathione metabolism, and phenylpropanoid biosynthesis. The proteomics results were validated with real-time qRT-PCR analysis. We were also able to identify the complete coding sequences for all the proteins of which few selected genes were cloned and sequence characterized for further confirmation. Our study is the first report of a quantitative proteomics dataset in black pepper which provides convincing evidence on the effectiveness of a transcriptome-based label-free proteomics approach for elucidating the host response to biotic stress in a non-model spice crop like P. nigrum, for which genome information is unavailable. Our dataset will serve as a useful resource for future studies in this plant. Data are available via ProteomeXchange with identifier PXD003887. PMID:27379110

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

PubMed

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

2016-01-01

Black pepper (Piper nigrum L.), a tropical spice crop of global acclaim, is susceptible to Phytophthora capsici, an oomycete pathogen which causes the highly destructive foot rot disease. A systematic understanding of this phytopathosystem has not been possible owing to lack of genome or proteome information. In this study, we explain an integrated transcriptome-assisted label-free quantitative proteomics pipeline to study the basal immune components of black pepper when challenged with P. capsici. We report a global identification of 532 novel leaf proteins from black pepper, of which 518 proteins were functionally annotated using BLAST2GO tool. A label-free quantitation of the protein datasets revealed 194 proteins common to diseased and control protein datasets of which 22 proteins showed significant up-regulation and 134 showed significant down-regulation. Ninety-three proteins were identified exclusively on P. capsici infected leaf tissues and 245 were expressed only in mock (control) infected samples. In-depth analysis of our data gives novel insights into the regulatory pathways of black pepper which are compromised during the infection. Differential down-regulation was observed in a number of critical pathways like carbon fixation in photosynthetic organism, cyano-amino acid metabolism, fructose, and mannose metabolism, glutathione metabolism, and phenylpropanoid biosynthesis. The proteomics results were validated with real-time qRT-PCR analysis. We were also able to identify the complete coding sequences for all the proteins of which few selected genes were cloned and sequence characterized for further confirmation. Our study is the first report of a quantitative proteomics dataset in black pepper which provides convincing evidence on the effectiveness of a transcriptome-based label-free proteomics approach for elucidating the host response to biotic stress in a non-model spice crop like P. nigrum, for which genome information is unavailable. Our dataset will serve as a useful resource for future studies in this plant. Data are available via ProteomeXchange with identifier PXD003887.

Metabolomics method to comprehensively analyze amino acids in different domains.

PubMed

Gu, Haiwei; Du, Jianhai; Carnevale Neto, Fausto; Carroll, Patrick A; Turner, Sally J; Chiorean, E Gabriela; Eisenman, Robert N; Raftery, Daniel

2015-04-21

Amino acids play essential roles in both metabolism and the proteome. Many studies have profiled free amino acids (FAAs) or proteins; however, few have connected the measurement of FAA with individual amino acids in the proteome. In this study, we developed a metabolomics method to comprehensively analyze amino acids in different domains, using two examples of different sample types and disease models. We first examined the responses of FAAs and insoluble-proteome amino acids (IPAAs) to the Myc oncogene in Tet21N human neuroblastoma cells. The metabolic and proteomic amino acid profiles were quite different, even under the same Myc condition, and their combination provided a better understanding of the biological status. In addition, amino acids were measured in 3 domains (FAAs, free and soluble-proteome amino acids (FSPAAs), and IPAAs) to study changes in serum amino acid profiles related to colon cancer. A penalized logistic regression model based on the amino acids from the three domains had better sensitivity and specificity than that from each individual domain. To the best of our knowledge, this is the first study to perform a combined analysis of amino acids in different domains, and indicates the useful biological information available from a metabolomics analysis of the protein pellet. This study lays the foundation for further quantitative tracking of the distribution of amino acids in different domains, with opportunities for better diagnosis and mechanistic studies of various diseases.

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

PubMed

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

2010-08-15

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

Less label, more free: approaches in label-free quantitative mass spectrometry.

PubMed

Neilson, Karlie A; Ali, Naveid A; Muralidharan, Sridevi; Mirzaei, Mehdi; Mariani, Michael; Assadourian, Gariné; Lee, Albert; van Sluyter, Steven C; Haynes, Paul A

2011-02-01

In this review we examine techniques, software, and statistical analyses used in label-free quantitative proteomics studies for area under the curve and spectral counting approaches. Recent advances in the field are discussed in an order that reflects a logical workflow design. Examples of studies that follow this design are presented to highlight the requirement for statistical assessment and further experiments to validate results from label-free quantitation. Limitations of label-free approaches are considered, label-free approaches are compared with labelling techniques, and forward-looking applications for label-free quantitative data are presented. We conclude that label-free quantitative proteomics is a reliable, versatile, and cost-effective alternative to labelled quantitation. Copyright © 2011 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Neutron-Encoded Protein Quantification by Peptide Carbamylation

NASA Astrophysics Data System (ADS)

Ulbrich, Arne; Merrill, Anna E.; Hebert, Alexander S.; Westphall, Michael S.; Keller, Mark P.; Attie, Alan D.; Coon, Joshua J.

2014-01-01

We describe a chemical tag for duplex proteome quantification using neutron encoding (NeuCode). The method utilizes the straightforward, efficient, and inexpensive carbamylation reaction. We demonstrate the utility of NeuCode carbamylation by accurately measuring quantitative ratios from tagged yeast lysates mixed in known ratios and by applying this method to quantify differential protein expression in mice fed a either control or high-fat diet.

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

PubMed

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

2015-05-01

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

The impact of carbon-13 and deuterium on relative quantification of proteins using stable isotope diethyl labeling.

PubMed

Koehler, Christian J; Arntzen, Magnus Ø; Thiede, Bernd

2015-05-15

Stable isotopic labeling techniques are useful for quantitative proteomics. A cost-effective and convenient method for diethylation by reductive amination was established. The impact using either carbon-13 or deuterium on quantification accuracy and precision was investigated using diethylation. We established an effective approach for stable isotope labeling by diethylation of amino groups of peptides. The approach was validated using matrix-assisted laser desorption/ionization time-of-flight (MALDI-TOF) and nanospray liquid chromatography/electrospray ionization (nanoLC/ESI)-ion trap/orbitrap for mass spectrometric analysis as well as MaxQuant for quantitative data analysis. Reaction conditions with low reagent costs, high yields and minor side reactions were established for diethylation. Furthermore, we showed that diethylation can be applied to up to sixplex labeling. For duplex experiments, we compared diethylation in the analysis of the proteome of HeLa cells using acetaldehyde-(13) C(2)/(12) C(2) and acetaldehyde-(2) H(4)/(1) H(4). Equal numbers of proteins could be identified and quantified; however, (13) C(4)/(12) C(4) -diethylation revealed a lower variance of quantitative peptide ratios within proteins resulting in a higher precision of quantified proteins and less falsely regulated proteins. The results were compared with dimethylation showing minor effects because of the lower number of deuteriums. The described approach for diethylation of primary amines is a cost-effective and accurate method for up to sixplex relative quantification of proteomes. (13) C(4)/(12) C(4) -diethylation enables duplex quantification based on chemical labeling without using deuterium which reduces identification of false-negatives and increases the quality of the quantification results. Copyright © 2015 John Wiley & Sons, Ltd.

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

PubMed

Holland, Ashling

2018-01-01

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

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

PubMed

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

2013-12-01

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

Maillard Proteomics: Opening New Pages

PubMed Central

Soboleva, Alena; Schmidt, Rico; Vikhnina, Maria; Grishina, Tatiana; Frolov, Andrej

2017-01-01

Protein glycation is a ubiquitous non-enzymatic post-translational modification, formed by reaction of protein amino and guanidino groups with carbonyl compounds, presumably reducing sugars and α-dicarbonyls. Resulting advanced glycation end products (AGEs) represent a highly heterogeneous group of compounds, deleterious in mammals due to their pro-inflammatory effect, and impact in pathogenesis of diabetes mellitus, Alzheimer’s disease and ageing. The body of information on the mechanisms and pathways of AGE formation, acquired during the last decades, clearly indicates a certain site-specificity of glycation. It makes characterization of individual glycation sites a critical pre-requisite for understanding in vivo mechanisms of AGE formation and developing adequate nutritional and therapeutic approaches to reduce it in humans. In this context, proteomics is the methodology of choice to address site-specific molecular changes related to protein glycation. Therefore, here we summarize the methods of Maillard proteomics, specifically focusing on the techniques providing comprehensive structural and quantitative characterization of glycated proteome. Further, we address the novel break-through areas, recently established in the field of Maillard research, i.e., in vitro models based on synthetic peptides, site-based diagnostics of metabolism-related diseases (e.g., diabetes mellitus), proteomics of anti-glycative defense, and dynamics of plant glycated proteome during ageing and response to environmental stress. PMID:29231845

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.

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.

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

PubMed

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

2014-08-01

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

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

PubMed

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

2013-01-04

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

Quantitative Proteomic Analyses of Staphylococcus aureus Treated with Punicalagin, a Natural Antibiotic from Pomegranate that Disrupts Iron Homeostasis and Induces SOS

USDA-ARS?s Scientific Manuscript database

Staphylococcus aureus, a bacterial, food-borne pathogen of humans, can contaminate raw fruits and vegetables. While physical and chemical methods are available to control S. aureus, scientists are searching for inhibitory phytochemicals from plants. One promising compound from pomegranate is punica...

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

PubMed

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

2017-03-01

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

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.

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

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

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

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

Teaching Expression Proteomics: From the Wet-Lab to the Laptop

ERIC Educational Resources Information Center

Teixeira, Miguel C.; Santos, Pedro M.; Rodrigues, Catarina; Sa-Correia, Isabel

2009-01-01

Expression proteomics has become, in recent years, a key genome-wide expression approach in fundamental and applied life sciences. This postgenomic technology aims the quantitative analysis of all the proteins or protein forms (the so-called proteome) of a given organism in a given environmental and genetic context. It is a challenge to provide…

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

PubMed

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

2014-03-07

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

Quantitative Characterization of Major Hepatic UDP-Glucuronosyltransferase Enzymes in Human Liver Microsomes: Comparison of Two Proteomic Methods and Correlation with Catalytic Activity.

PubMed

Achour, Brahim; Dantonio, Alyssa; Niosi, Mark; Novak, Jonathan J; Fallon, John K; Barber, Jill; Smith, Philip C; Rostami-Hodjegan, Amin; Goosen, Theunis C

2017-10-01

Quantitative characterization of UDP-glucuronosyltransferase (UGT) enzymes is valuable in glucuronidation reaction phenotyping, predicting metabolic clearance and drug-drug interactions using extrapolation exercises based on pharmacokinetic modeling. Different quantitative proteomic workflows have been employed to quantify UGT enzymes in various systems, with reports indicating large variability in expression, which cannot be explained by interindividual variability alone. To evaluate the effect of methodological differences on end-point UGT abundance quantification, eight UGT enzymes were quantified in 24 matched liver microsomal samples by two laboratories using stable isotope-labeled (SIL) peptides or quantitative concatemer (QconCAT) standard, and measurements were assessed against catalytic activity in seven enzymes ( n = 59). There was little agreement between individual abundance levels reported by the two methods; only UGT1A1 showed strong correlation [Spearman rank order correlation (Rs) = 0.73, P < 0.0001; R 2 = 0.30; n = 24]. SIL-based abundance measurements correlated well with enzyme activities, with correlations ranging from moderate for UGTs 1A6, 1A9, and 2B15 (Rs = 0.52-0.59, P < 0.0001; R 2 = 0.34-0.58; n = 59) to strong correlations for UGTs 1A1, 1A3, 1A4, and 2B7 (Rs = 0.79-0.90, P < 0.0001; R 2 = 0.69-0.79). QconCAT-based data revealed generally poor correlation with activity, whereas moderate correlations were shown for UGTs 1A1, 1A3, and 2B7. Spurious abundance-activity correlations were identified in the cases of UGT1A4/2B4 and UGT2B7/2B15, which could be explained by correlations of protein expression between these enzymes. Consistent correlation of UGT abundance with catalytic activity, demonstrated by the SIL-based dataset, suggests that quantitative proteomic data should be validated against catalytic activity whenever possible. In addition, metabolic reaction phenotyping exercises should consider spurious abundance-activity correlations to avoid misleading conclusions. Copyright © 2017 by The American Society for Pharmacology and Experimental Therapeutics.

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

PubMed Central

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

2013-01-01

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

Analysis of the variability of human normal urine by 2D-GE reveals a "public" and a "private" proteome.

PubMed

Molina, Laurence; Salvetat, Nicolas; Ameur, Randa Ben; Peres, Sabine; Sommerer, Nicolas; Jarraya, Fayçal; Ayadi, Hammadi; Molina, Franck; Granier, Claude

2011-12-10

The characterization of the normal urinary proteome is steadily progressing and represents a major interest in the assessment of clinical urinary biomarkers. To estimate quantitatively the variability of the normal urinary proteome, urines of 20 healthy people were collected. We first evaluated the impact of the sample conservation temperature on urine proteome integrity. Keeping the urine sample at RT or at +4°C until storage at -80°C seems the best way for long-term storage of samples for 2D-GE analysis. The quantitative variability of the normal urinary proteome was estimated on the 20 urines mapped by 2D-GE. The occurrence of the 910 identified spots was analysed throughout the gels and represented in a virtual 2D gel. Sixteen percent of the spots were found to occur in all samples and 23% occurred in at least 90% of urines. About 13% of the protein spots were present only in 10% or less of the samples, thus representing the most variable part of the normal urinary proteome. Twenty proteins corresponding to a fraction of the fully conserved spots were identified by mass spectrometry. In conclusion, a "public" urinary proteome, common to healthy individuals, seems to coexist with a "private" urinary proteome, which is more specific to each individual. Copyright © 2011 Elsevier B.V. All rights reserved.

A unique proteomic profile on surface IgM ligation in unmutated chronic lymphocytic leukemia

PubMed Central

Perrot, Aurore; Pionneau, Cédric; Nadaud, Sophie; Davi, Frédéric; Leblond, Véronique; Jacob, Frédéric; Merle-Béral, Hélène; Herbrecht, Raoul; Béné, Marie-Christine; Gribben, John G.; Vallat, Laurent

2011-01-01

Chronic lymphocytic leukemia (CLL) is characterized by a highly variable clinical course with 2 extreme subsets: indolent, ZAP70− and mutated immunoglobulin heavy chain gene (M-CLL); and aggressive, ZAP70+ and unmutated immunoglobulin heavy chain (UM-CLL). Given the long-term suspicion of antigenic stimulation as a primum movens in the disease, the role of the B-cell receptor has been extensively studied in various experimental settings; albeit scarcely in a comparative dynamic proteomic approach. Here we use a quantitative 2-dimensional fluorescence difference gel electrophoresis technology to compare 48 proteomic profiles of the 2 CLL subsets before and after anti-IgM ligation. Differentially expressed proteins were subsequently identified by mass spectrometry. We show that unstimulated M- and UM-CLL cells display distinct proteomic profiles. Furthermore, anti-IgM stimulation induces a specific proteomic response, more pronounced in the more aggressive CLL. Statistical analyses demonstrate several significant protein variations according to stimulation conditions. Finally, we identify an intermediate form of M-CLL cells, with an indolent profile (ZAP70−) but sharing aggressive proteomic profiles alike UM-CLL cells. Collectively, this first quantitative and dynamic proteome analysis of CLL further dissects the complex molecular pathway after B-cell receptor stimulation and depicts distinct proteomic profiles, which could lead to novel molecular stratification of the disease. PMID:21602524

Quantification of Flavin-containing Monooxygenases 1, 3, and 5 in Human Liver Microsomes by UPLC-MRM-Based Targeted Quantitative Proteomics and Its Application to the Study of Ontogeny.

PubMed

Chen, Yao; Zane, Nicole R; Thakker, Dhiren R; Wang, Michael Zhuo

2016-07-01

Flavin-containing monooxygenases (FMOs) have a significant role in the metabolism of small molecule pharmaceuticals. Among the five human FMOs, FMO1, FMO3, and FMO5 are the most relevant to hepatic drug metabolism. Although age-dependent hepatic protein expression, based on immunoquantification, has been reported previously for FMO1 and FMO3, there is very little information on hepatic FMO5 protein expression. To overcome the limitations of immunoquantification, an ultra-performance liquid chromatography (UPLC)-multiple reaction monitoring (MRM)-based targeted quantitative proteomic method was developed and optimized for the quantification of FMO1, FMO3, and FMO5 in human liver microsomes (HLM). A post-in silico product ion screening process was incorporated to verify LC-MRM detection of potential signature peptides before their synthesis. The developed method was validated by correlating marker substrate activity and protein expression in a panel of adult individual donor HLM (age 39-67 years). The mean (range) protein expression of FMO3 and FMO5 was 46 (26-65) pmol/mg HLM protein and 27 (11.5-49) pmol/mg HLM protein, respectively. To demonstrate quantification of FMO1, a panel of fetal individual donor HLM (gestational age 14-20 weeks) was analyzed. The mean (range) FMO1 protein expression was 7.0 (4.9-9.7) pmol/mg HLM protein. Furthermore, the ontogenetic protein expression of FMO5 was evaluated in fetal, pediatric, and adult HLM. The quantification of FMO proteins also was compared using two different calibration standards, recombinant proteins versus synthetic signature peptides, to assess the ratio between holoprotein versus total protein. In conclusion, a UPLC-MRM-based targeted quantitative proteomic method has been developed for the quantification of FMO enzymes in HLM. Copyright © 2016 by The American Society for Pharmacology and Experimental Therapeutics.

Quantification of Flavin-containing Monooxygenases 1, 3, and 5 in Human Liver Microsomes by UPLC-MRM-Based Targeted Quantitative Proteomics and Its Application to the Study of Ontogeny

PubMed Central

Chen, Yao; Zane, Nicole R.; Thakker, Dhiren R.

2016-01-01

Flavin-containing monooxygenases (FMOs) have a significant role in the metabolism of small molecule pharmaceuticals. Among the five human FMOs, FMO1, FMO3, and FMO5 are the most relevant to hepatic drug metabolism. Although age-dependent hepatic protein expression, based on immunoquantification, has been reported previously for FMO1 and FMO3, there is very little information on hepatic FMO5 protein expression. To overcome the limitations of immunoquantification, an ultra-performance liquid chromatography (UPLC)-multiple reaction monitoring (MRM)-based targeted quantitative proteomic method was developed and optimized for the quantification of FMO1, FMO3, and FMO5 in human liver microsomes (HLM). A post-in silico product ion screening process was incorporated to verify LC-MRM detection of potential signature peptides before their synthesis. The developed method was validated by correlating marker substrate activity and protein expression in a panel of adult individual donor HLM (age 39–67 years). The mean (range) protein expression of FMO3 and FMO5 was 46 (26–65) pmol/mg HLM protein and 27 (11.5–49) pmol/mg HLM protein, respectively. To demonstrate quantification of FMO1, a panel of fetal individual donor HLM (gestational age 14–20 weeks) was analyzed. The mean (range) FMO1 protein expression was 7.0 (4.9–9.7) pmol/mg HLM protein. Furthermore, the ontogenetic protein expression of FMO5 was evaluated in fetal, pediatric, and adult HLM. The quantification of FMO proteins also was compared using two different calibration standards, recombinant proteins versus synthetic signature peptides, to assess the ratio between holoprotein versus total protein. In conclusion, a UPLC-MRM-based targeted quantitative proteomic method has been developed for the quantification of FMO enzymes in HLM. PMID:26839369

A Novel Pulse-Chase SILAC Strategy Measures Changes in Protein Decay and Synthesis Rates Induced by Perturbation of Proteostasis with an Hsp90 Inhibitor

PubMed Central

Fierro-Monti, Ivo; Racle, Julien; Hernandez, Celine; Waridel, Patrice; Hatzimanikatis, Vassily; Quadroni, Manfredo

2013-01-01

Standard proteomics methods allow the relative quantitation of levels of thousands of proteins in two or more samples. While such methods are invaluable for defining the variations in protein concentrations which follow the perturbation of a biological system, they do not offer information on the mechanisms underlying such changes. Expanding on previous work [1], we developed a pulse-chase (pc) variant of SILAC (stable isotope labeling by amino acids in cell culture). pcSILAC can quantitate in one experiment and for two conditions the relative levels of proteins newly synthesized in a given time as well as the relative levels of remaining preexisting proteins. We validated the method studying the drug-mediated inhibition of the Hsp90 molecular chaperone, which is known to lead to increased synthesis of stress response proteins as well as the increased decay of Hsp90 “clients”. We showed that pcSILAC can give information on changes in global cellular proteostasis induced by treatment with the inhibitor, which are normally not captured by standard relative quantitation techniques. Furthermore, we have developed a mathematical model and computational framework that uses pcSILAC data to determine degradation constants kd and synthesis rates Vs for proteins in both control and drug-treated cells. The results show that Hsp90 inhibition induced a generalized slowdown of protein synthesis and an increase in protein decay. Treatment with the inhibitor also resulted in widespread protein-specific changes in relative synthesis rates, together with variations in protein decay rates. The latter were more restricted to individual proteins or protein families than the variations in synthesis. Our results establish pcSILAC as a viable workflow for the mechanistic dissection of changes in the proteome which follow perturbations. Data are available via ProteomeXchange with identifier PXD000538. PMID:24312217

Quantitative Molecular Phenotyping of Gill Remodeling in a Cichlid Fish Responding to Salinity Stress*

PubMed Central

Kültz, Dietmar; Li, Johnathon; Gardell, Alison; Sacchi, Romina

2013-01-01

A two-tiered label-free quantitative (LFQ) proteomics workflow was used to elucidate how salinity affects the molecular phenotype, i.e. proteome, of gills from a cichlid fish, the euryhaline tilapia (Oreochromis mossambicus). The workflow consists of initial global profiling of relative tryptic peptide abundances in treated versus control samples followed by targeted identification (by MS/MS) and quantitation (by chromatographic peak area integration) of validated peptides for each protein of interest. Fresh water acclimated tilapia were independently exposed in separate experiments to acute short-term (34 ppt) and gradual long-term (70 ppt, 90 ppt) salinity stress followed by molecular phenotyping of the gill proteome. The severity of salinity stress can be deduced with high technical reproducibility from the initial global label-free quantitative profiling step alone at both peptide and protein levels. However, an accurate regulation ratio can only be determined by targeted label-free quantitative profiling because not all peptides used for protein identification are also valid for quantitation. Of the three salinity challenges, gradual acclimation to 90 ppt has the most pronounced effect on gill molecular phenotype. Known salinity effects on tilapia gills, including an increase in the size and number of mitochondria-rich ionocytes, activities of specific ion transporters, and induction of specific molecular chaperones are reflected in the regulation of abundances of the corresponding proteins. Moreover, specific protein isoforms that are responsive to environmental salinity change are resolved and it is revealed that salinity effects on the mitochondrial proteome are nonuniform. Furthermore, protein NDRG1 has been identified as a novel key component of molecular phenotype restructuring during salinity-induced gill remodeling. In conclusion, besides confirming known effects of salinity on gills of euryhaline fish, molecular phenotyping reveals novel insight into proteome changes that underlie the remodeling of tilapia gill epithelium in response to environmental salinity change. PMID:24065692

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

PubMed Central

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

2016-01-01

To date, the proteomic profiling of Müller cells, the dominant macroglia of the retina, has been hampered because of the absence of suitable enrichment methods. We established a novel protocol to isolate native, intact Müller cells from adult murine retinae at excellent purity which retain in situ morphology and are well suited for proteomic analyses. Two different strategies of sample preparation - an in StageTips (iST) and a subcellular fractionation approach including cell surface protein profiling were used for quantitative liquid chromatography-mass spectrometry (LC-MSMS) comparing Müller cell-enriched to depleted neuronal fractions. Pathway enrichment analyses on both data sets enabled us to identify Müller cell-specific functions which included focal adhesion kinase signaling, signal transduction mediated by calcium as second messenger, transmembrane neurotransmitter transport and antioxidant activity. Pathways associated with RNA processing, cellular respiration and phototransduction were enriched in the neuronal subpopulation. Proteomic results were validated for selected Müller cell genes by quantitative real time PCR, confirming the high expression levels of numerous members of the angiogenic and anti-inflammatory annexins and antioxidant enzymes (e.g. paraoxonase 2, peroxiredoxin 1, 4 and 6). Finally, the significant enrichment of antioxidant proteins in Müller cells was confirmed by measurements on vital retinal cells using the oxidative stress indicator CM-H2DCFDA. In contrast to photoreceptors or bipolar cells, Müller cells were most efficiently protected against H2O2-induced reactive oxygen species formation, which is in line with the protein repertoire identified in the proteomic profiling. Our novel approach to isolate intact glial cells from adult retina in combination with proteomic profiling enabled the identification of novel Müller glia specific proteins, which were validated as markers and for their functional impact in glial physiology. This provides the basis to allow the discovery of novel glial specializations and will enable us to elucidate the role of Müller cells in retinal pathologies — a topic still controversially discussed. PMID:26324419

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

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

PubMed

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

2012-05-01

Neuroendocrine systems integrate both extrinsic and intrinsic signals to regulate virtually all aspects of an animal's physiology. In aquatic toxicology, studies have shown that pollutants are capable of disrupting the neuroendocrine system of teleost fish, and many chemicals found in the environment can also have a neurotoxic mode of action. Omics approaches are now used to better understand cell signaling cascades underlying fish neurophysiology and the control of pituitary hormone release, in addition to identifying adverse effects of pollutants in the teleostean central nervous system. For example, both high throughput genomics and proteomic investigations of molecular signaling cascades for both neurotransmitter and nuclear receptor agonists/antagonists have been reported. This review highlights recent studies that have utilized quantitative proteomics methods such as 2D differential in-gel electrophoresis (DIGE) and isobaric tagging for relative and absolute quantitation (iTRAQ) in neuroendocrine regions and uses these examples to demonstrate the challenges of using proteomics in neuroendocrinology and neurotoxicology research. To begin to characterize the teleost neuroproteome, we functionally annotated 623 unique proteins found in the fish hypothalamus and telencephalon. These proteins have roles in biological processes that include synaptic transmission, ATP production, receptor activity, cell structure and integrity, and stress responses. The biological processes most represented by proteins detected in the teleost neuroendocrine brain included transport (8.4%), metabolic process (5.5%), and glycolysis (4.8%). We provide an example of using sub-network enrichment analysis (SNEA) to identify protein networks in the fish hypothalamus in response to dopamine receptor signaling. Dopamine signaling altered the abundance of proteins that are binding partners of microfilaments, integrins, and intermediate filaments, consistent with data suggesting dopaminergic regulation of neuronal stability and structure. Lastly, for fish neuroendocrine studies using both high-throughput genomics and proteomics, we compare gene and protein relationships in the hypothalamus and demonstrate that correlation is often poor for single time point experiments. These studies highlight the need for additional time course analyses to better understand gene-protein relationships and adverse outcome pathways. This is important if both transcriptomics and proteomics are to be used together to investigate neuroendocrine signaling pathways or as bio-monitoring tools in ecotoxicology. Copyright © 2011 Elsevier Inc. All rights reserved.

Reproducibility of combinatorial peptide ligand libraries for proteome capture evaluated by selected reaction monitoring.

PubMed

Di Girolamo, Francesco; Righetti, Pier Giorgio; Soste, Martin; Feng, Yuehan; Picotti, Paola

2013-08-26

Systems biology studies require the capability to quantify with high precision proteins spanning a broad range of abundances across multiple samples. However, the broad range of protein expression in cells often precludes the detection of low-abundance proteins. Different sample processing techniques can be applied to increase proteome coverage. Among these, combinatorial (hexa)peptide ligand libraries (CPLLs) bound to solid matrices have been used to specifically capture and detect low-abundance proteins in complex samples. To assess whether CPLL capture can be applied in systems biology studies involving the precise quantitation of proteins across a multitude of samples, we evaluated its performance across the whole range of protein abundances in Saccharomyces cerevisiae. We used selected reaction monitoring assays for a set of target proteins covering a broad abundance range to quantitatively evaluate the precision of the approach and its capability to detect low-abundance proteins. Replicated CPLL-isolates showed an average variability of ~10% in the amount of the isolated proteins. The high reproducibility of the technique was not dependent on the abundance of the protein or the amount of beads used for the capture. However, the protein-to-bead ratio affected the enrichment of specific proteins. We did not observe a normalization effect of CPLL beads on protein abundances. However, CPLLs enriched for and depleted specific sets of proteins and thus changed the abundances of proteins from a whole proteome extract. This allowed the identification of ~400 proteins otherwise undetected in an untreated sample, under the experimental conditions used. CPLL capture is thus a useful tool to increase protein identifications in proteomic experiments, but it should be coupled to the analysis of untreated samples, to maximize proteome coverage. Our data also confirms that CPLL capture is reproducible and can be confidently used in quantitative proteomic experiments. Combinatorial hexapeptide ligand libraries (CPLLs) bound to solid matrices have been proposed to specifically capture and detect low-abundance proteins in complex samples. To assess whether the CPLL capture can be confidently applied in systems biology studies involving the precise quantitation of proteins across a broad range of abundances and a multitude of samples, we evaluated its reproducibility and performance features. Using selected reaction monitoring assays for proteins covering the whole range of abundances we show that the technique is reproducible and compatible with quantitative proteomic studies. However, the protein-to-bead ratio affects the enrichment of specific proteins and CPLLs depleted specific sets of proteins from a whole proteome extract. Our results suggest that CPLL-based analyses should be coupled to the analysis of untreated samples, to maximize proteome coverage. Overall, our data confirms the applicability of CPLLs in systems biology research and guides the correct use of this technique. Copyright © 2013 Elsevier B.V. All rights reserved.

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

PubMed

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

2016-04-14

Lung cancer currently ranks as the neoplasia with the highest global mortality rate. Although some improvements have been introduced in recent years, new advances in diagnosis are required in order to increase survival rates. New mildly invasive endoscopy-based diagnostic techniques include the collection of bronchoalveolar lavage fluid (BALF), which is discarded after using a portion of the fluid for standard pathological procedures. BALF proteomic analysis can contribute to clinical practice with more sensitive biomarkers, and can complement cytohistological studies by aiding in the diagnosis, prognosis, and subtyping of lung cancer, as well as the monitoring of treatment response. The range of quantitative proteomics methodologies used for biomarker discovery is currently being broadened with the introduction of data-independent acquisition (DIA) analysis-related approaches that address the massive quantitation of the components of a proteome. Here we report for the first time a DIA-based quantitative proteomics study using BALF as the source for the discovery of potential lung cancer biomarkers. The results have been encouraging in terms of the number of identified and quantified proteins. A panel of candidate protein biomarkers for adenocarcinoma in BALF is reported; this points to the activation of the complement network as being strongly over-represented and suggests this pathway as a potential target for lung cancer research. In addition, the results reported for haptoglobin, complement C4-A, and glutathione S-transferase pi are consistent with previous studies, which indicates that these proteins deserve further consideration as potential lung cancer biomarkers in BALF. Our study demonstrates that the analysis of BALF proteins by liquid chromatography-tandem mass spectrometry (LC-MS/MS), combining a simple sample pre-treatment and SWATH DIA MS, is a useful method for the discovery of potential lung cancer biomarkers. Bronchoalveolar lavage fluid (BALF) analysis can contribute to clinical practice with more sensitive biomarkers, thus complementing cytohistological studies in order to aid in the diagnosis, prognosis, and subtyping of lung cancer, as well as the monitoring of treatment response. Here we report a panel of candidate protein biomarkers for adenocarcinoma in BALF. Forty-four proteins showed a fold-change higher than 3.75 among adenocarcinoma patients compared with controls. This report is the first DIA-based quantitative proteomics study to use bronchoalveolar lavage fluid (BALF) as a matrix for discovering potential biomarkers. The results are encouraging in terms of the number of identified and quantified proteins, demonstrating that the analysis of BALF proteins by a SWATH approach is a useful method for the discovery of potential biomarkers of pulmonary diseases. Copyright © 2016 Elsevier B.V. All rights reserved.

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

PubMed Central

Anderson, Leigh

2005-01-01

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

Evaluation of several two-dimensional gel electrophoresis techniques in cardiac proteomics.

PubMed

Li, Zhao Bo; Flint, Paul W; Boluyt, Marvin O

2005-09-01

Two-dimensional gel electrophoresis (2-DE) is currently the best method for separating complex mixtures of proteins, and its use is gradually becoming more common in cardiac proteome analysis. A number of variations in basic 2-DE have emerged, but their usefulness in analyzing cardiac tissue has not been evaluated. The purpose of the present study was to systematically evaluate the capabilities and limitations of several 2-DE techniques for separating proteins from rat heart tissue. Immobilized pH gradient strips of various pH ranges, parameters of protein loading and staining, subcellular fractionation, and detection of phosphorylated proteins were studied. The results provide guidance for proteome analysis of cardiac and other tissues in terms of selection of the isoelectric point separating window for cardiac proteins, accurate quantitation of cardiac protein abundance, stabilization of technical variation, reduction of sample complexity, enrichment of low-abundant proteins, and detection of phosphorylated proteins.

Detection of dysregulated protein-association networks by high-throughput proteomics predicts cancer vulnerabilities.

PubMed

Lapek, John D; Greninger, Patricia; Morris, Robert; Amzallag, Arnaud; Pruteanu-Malinici, Iulian; Benes, Cyril H; Haas, Wilhelm

2017-10-01

The formation of protein complexes and the co-regulation of the cellular concentrations of proteins are essential mechanisms for cellular signaling and for maintaining homeostasis. Here we use isobaric-labeling multiplexed proteomics to analyze protein co-regulation and show that this allows the identification of protein-protein associations with high accuracy. We apply this 'interactome mapping by high-throughput quantitative proteome analysis' (IMAHP) method to a panel of 41 breast cancer cell lines and show that deviations of the observed protein co-regulations in specific cell lines from the consensus network affects cellular fitness. Furthermore, these aberrant interactions serve as biomarkers that predict the drug sensitivity of cell lines in screens across 195 drugs. We expect that IMAHP can be broadly used to gain insight into how changing landscapes of protein-protein associations affect the phenotype of biological systems.

The Expanding Landscape of the Thiol Redox Proteome*

PubMed Central

Yang, Jing; Carroll, Kate S.; Liebler, Daniel C.

2016-01-01

Cysteine occupies a unique place in protein chemistry. The nucleophilic thiol group allows cysteine to undergo a broad range of redox modifications beyond classical thiol-disulfide redox equilibria, including S-sulfenylation (-SOH), S-sulfinylation (-SO2H), S-sulfonylation (-SO3H), S-nitrosylation (-SNO), S-sulfhydration (-SSH), S-glutathionylation (-SSG), and others. Emerging evidence suggests that these post-translational modifications (PTM) are important in cellular redox regulation and protection against oxidative damage. Identification of protein targets of thiol redox modifications is crucial to understanding their roles in biology and disease. However, analysis of these highly labile and dynamic modifications poses challenges. Recent advances in the design of probes for thiol redox forms, together with innovative mass spectrometry based chemoproteomics methods make it possible to perform global, site-specific, and quantitative analyses of thiol redox modifications in complex proteomes. Here, we review chemical proteomic strategies used to expand the landscape of thiol redox modifications. PMID:26518762

Application of targeted quantitative proteomics analysis in human cerebrospinal fluid using a liquid chromatography matrix-assisted laser desorption/ionization time-of-flight tandem mass spectrometer (LC MALDI TOF/TOF) platform.

PubMed

Pan, Sheng; Rush, John; Peskind, Elaine R; Galasko, Douglas; Chung, Kathryn; Quinn, Joseph; Jankovic, Joseph; Leverenz, James B; Zabetian, Cyrus; Pan, Catherine; Wang, Yan; Oh, Jung Hun; Gao, Jean; Zhang, Jianpeng; Montine, Thomas; Zhang, Jing

2008-02-01

Targeted quantitative proteomics by mass spectrometry aims to selectively detect one or a panel of peptides/proteins in a complex sample and is particularly appealing for novel biomarker verification/validation because it does not require specific antibodies. Here, we demonstrated the application of targeted quantitative proteomics in searching, identifying, and quantifying selected peptides in human cerebrospinal spinal fluid (CSF) using a matrix-assisted laser desorption/ionization time-of-flight tandem mass spectrometer (MALDI TOF/TOF)-based platform. The approach involved two major components: the use of isotopic-labeled synthetic peptides as references for targeted identification and quantification and a highly selective mass spectrometric analysis based on the unique characteristics of the MALDI instrument. The platform provides high confidence for targeted peptide detection in a complex system and can potentially be developed into a high-throughput system. Using the liquid chromatography (LC) MALDI TOF/TOF platform and the complementary identification strategy, we were able to selectively identify and quantify a panel of targeted peptides in the whole proteome of CSF without prior depletion of abundant proteins. The effectiveness and robustness of the approach associated with different sample complexity, sample preparation strategies, as well as mass spectrometric quantification were evaluated. Other issues related to chromatography separation and the feasibility for high-throughput analysis were also discussed. Finally, we applied targeted quantitative proteomics to analyze a subset of previously identified candidate markers in CSF samples of patients with Parkinson's disease (PD) at different stages and Alzheimer's disease (AD) along with normal controls.

Striking against bioterrorism with advanced proteomics and reference methods.

PubMed

Armengaud, Jean

2017-01-01

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

Comparative evaluation of saliva collection methods for proteome analysis.

PubMed

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

2013-04-18

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

The role of proteomics in studies of protein moonlighting.

PubMed

Beynon, Robert J; Hammond, Dean; Harman, Victoria; Woolerton, Yvonne

2014-12-01

The increasing acceptance that proteins may exert multiple functions in the cell brings with it new analytical challenges that will have an impact on the field of proteomics. Many proteomics workflows begin by destroying information about the interactions between different proteins, and the reduction of a complex protein mixture to constituent peptides also scrambles information about the combinatorial potential of post-translational modifications. To bring the focus of proteomics on to the domain of protein moonlighting will require novel analytical and quantitative approaches.

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

PubMed

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

2017-02-03

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

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

PubMed

Terzi, F; Cambridge, S

2017-01-01

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

Quantitative proteomic analysis of intact plastids.

PubMed

Shiraya, Takeshi; Kaneko, Kentaro; Mitsui, Toshiaki

2014-01-01

Plastids are specialized cell organelles in plant cells that are differentiated into various forms including chloroplasts, chromoplasts, and amyloplasts, and fulfill important functions in maintaining the overall cell metabolism and sensing environmental factors such as sunlight. It is therefore important to grasp the mechanisms of differentiation and functional changes of plastids in order to enhance the understanding of vegetality. In this chapter, details of a method for the extraction of intact plastids that makes analysis possible while maintaining the plastid functions are provided; in addition, a quantitative shotgun method for analyzing the composition and changes in the content of proteins in plastids as a result of environmental impacts is described.

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.

Alterations in brain cerebral cortex proteome of rabies-infected cat.

PubMed

Kasempimolporn, Songsri; Lumlertdacha, Boonlert; Chulasugandha, Pannipa; Boonchang, Supatsorn; Sitprija, Visith

2014-07-01

Comparative proteome analysis using brain cerebral cortex tissues from cats and dogs infected with/without rabies virus were conducted using both two-dimensional gel-electrophoresis (2-DE) and 2-D fluorescence difference gel- electrophoresis (2D-DIGE) methods. The 2-DE gel images of all samples revealed >1,000 protein spots in each gel. Quantitative intensity analysis revealed the same overall protein pattern in certain regions of the gel, but the rabies-infected brains exhibited more protein spots than the non-infected controls. From approximately 880 protein spots detected by 2D-DIGE, 65 protein spots were increased and 46 were decreased. Eight of these protein spots were randomly selected and annotated by reference to previous known proteome data of rabid dog brains. They were similarly altered in both of the rabies-infected cats and dogs. A more detailed comparison of changes in proteomic profiles of brains between rabid cats and dogs should shed some light on the pathophysiological mechanism of rabies in domestic animals, as most rabies cases have been traceable to or believed to have originated from rabid dogs.

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

PubMed

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

2013-06-15

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

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

PubMed Central

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

2006-01-01

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

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.

Large scale systematic proteomic quantification from non-metastatic to metastatic colorectal cancer

NASA Astrophysics Data System (ADS)

Yin, Xuefei; Zhang, Yang; Guo, Shaowen; Jin, Hong; Wang, Wenhai; Yang, Pengyuan

2015-07-01

A systematic proteomic quantification of formalin-fixed, paraffin-embedded (FFPE) colorectal cancer tissues from stage I to stage IIIC was performed in large scale. 1017 proteins were identified with 338 proteins in quantitative changes by label free method, while 341 proteins were quantified with significant expression changes among 6294 proteins by iTRAQ method. We found that proteins related to migration expression increased and those for binding and adherent decreased during the colorectal cancer development according to the gene ontology (GO) annotation and ingenuity pathway analysis (IPA). The integrin alpha 5 (ITA5) in integrin family was focused, which was consistent with the metastasis related pathway. The expression level of ITA5 decreased in metastasis tissues and the result has been further verified by Western blotting. Another two cell migration related proteins vitronectin (VTN) and actin-related protein (ARP3) were also proved to be up-regulated by both mass spectrometry (MS) based quantification results and Western blotting. Up to now, our result shows one of the largest dataset in colorectal cancer proteomics research. Our strategy reveals a disease driven omics-pattern for the metastasis colorectal cancer.

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

PubMed

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

2015-10-20

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

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

PubMed

Alvarez, Sophie; Roy Choudhury, Swarup; Hicks, Leslie M; Pandey, Sona

2013-03-01

Abscisic acid (ABA) is proposed to be perceived by multiple receptors in plants. We have previously reported on the role of two GPCR-type G-proteins (GTG proteins) as plasma membrane-localized ABA receptors in Arabidopsis thaliana. However, due to the presence of multiple transmembrane domains, detailed structural and biochemical characterization of GTG proteins remains limited. Since ABA induces substantial changes in the proteome of plants, a labeling LC-based quantitative proteomics approach was applied to elucidate the global effects and possible downstream targets of GTG1/GTG2 proteins. Quantitative differences in protein abundance between wild-type and gtg1gtg2 were analyzed for evaluation of the effect of ABA on the root proteome and its dependence on the presence of functional GTG1/GTG2 proteins. The results presented in this study reveal the most comprehensive ABA-responsive root proteome reported to date in Arabidopsis. Notably, the majority of ABA-responsive proteins required the presence of GTG proteins, supporting their key role in ABA signaling. These observations were further confirmed by additional experiments. Overall, comparison of the ABA-dependent protein abundance changes in wild-type versus gtg1gtg2 provides clues to their possible links with some of the well-established effectors of the ABA signaling pathways and their role in mediating phytohormone cross-talk.

Persulfidation proteome reveals the regulation of protein function by hydrogen sulfide in diverse biological processes in Arabidopsis.

PubMed

Aroca, Angeles; Benito, Juan M; Gotor, Cecilia; Romero, Luis C

2017-10-13

Hydrogen sulfide-mediated signaling pathways regulate many physiological and pathophysiological processes in mammalian and plant systems. The molecular mechanism by which hydrogen sulfide exerts its action involves the post-translational modification of cysteine residues to form a persulfidated thiol motif, a process called protein persulfidation. We have developed a comparative and quantitative proteomic analysis approach for the detection of endogenous persulfidated proteins in wild-type Arabidopsis and L-CYSTEINE DESULFHYDRASE 1 mutant leaves using the tag-switch method. The 2015 identified persulfidated proteins were isolated from plants grown under controlled conditions, and therefore, at least 5% of the entire Arabidopsis proteome may undergo persulfidation under baseline conditions. Bioinformatic analysis revealed that persulfidated cysteines participate in a wide range of biological functions, regulating important processes such as carbon metabolism, plant responses to abiotic and biotic stresses, plant growth and development, and RNA translation. Quantitative analysis in both genetic backgrounds reveals that protein persulfidation is mainly involved in primary metabolic pathways such as the tricarboxylic acid cycle, glycolysis, and the Calvin cycle, suggesting that this protein modification is a new regulatory component in these pathways. © The Author 2017. Published by Oxford University Press on behalf of the Society for Experimental Biology.

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

PubMed Central

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

2016-01-01

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

Proteomic analysis of hair shafts from monozygotic twins: Expression profiles and genetically variant peptides.

PubMed

Wu, Pei-Wen; Mason, Katelyn E; Durbin-Johnson, Blythe P; Salemi, Michelle; Phinney, Brett S; Rocke, David M; Parker, Glendon J; Rice, Robert H

2017-07-01

Forensic association of hair shaft evidence with individuals is currently assessed by comparing mitochondrial DNA haplotypes of reference and casework samples, primarily for exclusionary purposes. Present work tests and validates more recent proteomic approaches to extract quantitative transcriptional and genetic information from hair samples of monozygotic twin pairs, which would be predicted to partition away from unrelated individuals if the datasets contain identifying information. Protein expression profiles and polymorphic, genetically variant hair peptides were generated from ten pairs of monozygotic twins. Profiling using the protein tryptic digests revealed that samples from identical twins had typically an order of magnitude fewer protein expression differences than unrelated individuals. The data did not indicate that the degree of difference within twin pairs increased with age. In parallel, data from the digests were used to detect genetically variant peptides that result from common nonsynonymous single nucleotide polymorphisms in genes expressed in the hair follicle. Compilation of the variants permitted sorting of the samples by hierarchical clustering, permitting accurate matching of twin pairs. The results demonstrate that genetic differences are detectable by proteomic methods and provide a framework for developing quantitative statistical estimates of personal identification that increase the value of hair shaft evidence. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Changes in the Plasma Proteome Follows Chronic Opiate Administration In Simian Immunodeficiency Virus Infected Rhesus Macaques*

PubMed Central

Wiederin, Jayme L.; Yu, Fang; Donahoe, Robert M.; Fox, Howard S.; Ciborowski, Pawel; Gendelman, Howard E.

2011-01-01

Background Substantive plasma proteomic changes follow lentiviral infection and disease pathobiology. We posit that such protein alterations are modified during drug abuse, further serving to affect the disease. To this end, we investigated the effect of opiate administration on the plasma proteome of Indian-strain rhesus monkeys infected with simian immunodeficiency virus (SIV) strain smm9. Methods Whole blood was collected at 7 weeks prior to and 1.4 and 49 weeks after viral infection. Viral load, CD4+ T cell subsets, and plasma protein content were measured from monkeys that did or did not receive continuous opiate administrations. The plasma proteome was identified and quantified by isobaric tags for relative and absolute quantitation labeling (iTRAQ) and mass spectrometry. Results While substantive changes in plasma proteins were seen during SIV infection, the addition of opiates led to suppression of these changes as well as increased variance of the proteome. These changes demonstrate that opiates induce broad but variant immune suppression in SIV-infected monkeys. Conclusion The broad suppressive changes seen in plasma of SIV-infected monkeys likely reflect reduced multisystem immune homeostatic responses induced by opiates. Such occur as a consequence of complex cell-to-cell interactions operative between the virus and the host. We conclude that such changes in plasma proteomic profiling may be underappreciated and as such supports the need for improved clinical definitions. PMID:21821369

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

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

PubMed

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

2014-10-01

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

Decoding 2D-PAGE complex maps: relevance to proteomics.

PubMed

Pietrogrande, Maria Chiara; Marchetti, Nicola; Dondi, Francesco; Righetti, Pier Giorgio

2006-03-20

This review describes two mathematical approaches useful for decoding the complex signal of 2D-PAGE maps of protein mixtures. These methods are helpful for interpreting the large amount of data of each 2D-PAGE map by extracting all the analytical information hidden therein by spot overlapping. Here the basic theory and application to 2D-PAGE maps are reviewed: the means for extracting information from the experimental data and their relevance to proteomics are discussed. One method is based on the quantitative theory of statistical model of peak overlapping (SMO) using the spot experimental data (intensity and spatial coordinates). The second method is based on the study of the 2D-autocovariance function (2D-ACVF) computed on the experimental digitised map. They are two independent methods that are able to extract equal and complementary information from the 2D-PAGE map. Both methods permit to obtain fundamental information on the sample complexity and the separation performance and to single out ordered patterns present in spot positions: the availability of two independent procedures to compute the same separation parameters is a powerful tool to estimate the reliability of the obtained results. The SMO procedure is an unique tool to quantitatively estimate the degree of spot overlapping present in the map, while the 2D-ACVF method is particularly powerful in simply singling out the presence of order in the spot position from the complexity of the whole 2D map, i.e., spot trains. The procedures were validated by extensive numerical computation on computer-generated maps describing experimental 2D-PAGE gels of protein mixtures. Their applicability to real samples was tested on reference maps obtained from literature sources. The review describes the most relevant information for proteomics: sample complexity, separation performance, overlapping extent, identification of spot trains related to post-translational modifications (PTMs).

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

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

Liu, Xing; Xu, Yanli; Meng, Qian

Colorectal cancer (CRC) is one of the most common types of malignant tumor worldwide. Currently, although many researchers have been devoting themselves in CRC studies, the process of locating biomarkers for CRC early diagnosis and prognostic is still very slow. Using a centrifugal proteomic reactor-based proteomic analysis of minute amount of colonic biopsies by enteroscopy sampling, 2620 protein groups were quantified between cancer mucosa and adjacent normal colorectal mucosa. Of which, 403 protein groups were differentially expressed with statistic significance between cancer and normal tissues, including 195 up-regulated and 208 down-regulated proteins in cancer tissues. Three proteins (SOD3, PRELP andmore » NGAL) were selected for further Western blot validation. And the resulting Western blot experimental results were consistent with the quantitative proteomic data. SOD3 and PRELP are down-regulated in CRC mucosa comparing to adjacent normal tissue, while NGAL is up-regulated in CRC mucosa. In conclusion, the centrifugal proteomic reactor-based label-free quantitative proteomic approach provides a highly sensitive and powerful tool for analyzing minute protein sample from tiny colorectal biopsies, which may facilitate CRC biomarkers discovery for diagnoses and prognoses. -- Highlights: •Minute amount of colonic biopsies by endoscopy is suitable for proteomic analysis. •Centrifugal proteomic reactor can be used for processing tiny clinic biopsy sample. •SOD3 and PRELP are down-regulated in CRC, while NGAL is up-regulated in CRC.« less

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

PubMed

Arntzen, Magnus Ø; Koehler, Christian J; Barsnes, Harald; Berven, Frode S; Treumann, Achim; Thiede, Bernd

2011-02-04

Isobaric peptide labeling plays an important role in relative quantitative comparisons of proteomes. Isobaric labeling techniques utilize MS/MS spectra for relative quantification, which can be either based on the relative intensities of reporter ions in the low mass region (iTRAQ and TMT) or on the relative intensities of quantification signatures throughout the spectrum due to isobaric peptide termini labeling (IPTL). Due to the increased quantitative information found in MS/MS fragment spectra generated by the recently developed IPTL approach, new software was required to extract the quantitative information. IsobariQ was specifically developed for this purpose; however, support for the reporter ion techniques iTRAQ and TMT is also included. In addition, to address recently emphasized issues about heterogeneity of variance in proteomics data sets, IsobariQ employs the statistical software package R and variance stabilizing normalization (VSN) algorithms available therein. Finally, the functionality of IsobariQ is validated with data sets of experiments using 6-plex TMT and IPTL. Notably, protein substrates resulting from cleavage by proteases can be identified as shown for caspase targets in apoptosis.

Thermo-msf-parser: an open source Java library to parse and visualize Thermo Proteome Discoverer msf files.

PubMed

Colaert, Niklaas; Barsnes, Harald; Vaudel, Marc; Helsens, Kenny; Timmerman, Evy; Sickmann, Albert; Gevaert, Kris; Martens, Lennart

2011-08-05

The Thermo Proteome Discoverer program integrates both peptide identification and quantification into a single workflow for peptide-centric proteomics. Furthermore, its close integration with Thermo mass spectrometers has made it increasingly popular in the field. Here, we present a Java library to parse the msf files that constitute the output of Proteome Discoverer. The parser is also implemented as a graphical user interface allowing convenient access to the information found in the msf files, and in Rover, a program to analyze and validate quantitative proteomics information. All code, binaries, and documentation is freely available at http://thermo-msf-parser.googlecode.com.

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

PubMed Central

Chen, Yi-Hau

2017-01-01

Approaches to identify significant pathways from high-throughput quantitative data have been developed in recent years. Still, the analysis of proteomic data stays difficult because of limited sample size. This limitation also leads to the practice of using a competitive null as common approach; which fundamentally implies genes or proteins as independent units. The independent assumption ignores the associations among biomolecules with similar functions or cellular localization, as well as the interactions among them manifested as changes in expression ratios. Consequently, these methods often underestimate the associations among biomolecules and cause false positives in practice. Some studies incorporate the sample covariance matrix into the calculation to address this issue. However, sample covariance may not be a precise estimation if the sample size is very limited, which is usually the case for the data produced by mass spectrometry. In this study, we introduce a multivariate test under a self-contained null to perform pathway analysis for quantitative proteomic data. The covariance matrix used in the test statistic is constructed by the confidence scores retrieved from the STRING database or the HitPredict database. We also design an integrating procedure to retain pathways of sufficient evidence as a pathway group. The performance of the proposed T2-statistic is demonstrated using five published experimental datasets: the T-cell activation, the cAMP/PKA signaling, the myoblast differentiation, and the effect of dasatinib on the BCR-ABL pathway are proteomic datasets produced by mass spectrometry; and the protective effect of myocilin via the MAPK signaling pathway is a gene expression dataset of limited sample size. Compared with other popular statistics, the proposed T2-statistic yields more accurate descriptions in agreement with the discussion of the original publication. We implemented the T2-statistic into an R package T2GA, which is available at https://github.com/roqe/T2GA. PMID:28622336

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

PubMed

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

2017-06-01

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

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

PubMed Central

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

2012-01-01

Measuring the properties of endogenous cell proteins, such as expression level, subcellular localization, and turnover rates, on a whole proteome level remains a major challenge in the postgenome era. Quantitative methods for measuring mRNA expression do not reliably predict corresponding protein levels and provide little or no information on other protein properties. Here we describe a combined pulse-labeling, spatial proteomics and data analysis strategy to characterize the expression, localization, synthesis, degradation, and turnover rates of endogenously expressed, untagged human proteins in different subcellular compartments. Using quantitative mass spectrometry and stable isotope labeling with amino acids in cell culture, a total of 80,098 peptides from 8,041 HeLa proteins were quantified, and their spatial distribution between the cytoplasm, nucleus and nucleolus determined and visualized using specialized software tools developed in PepTracker. Using information from ion intensities and rates of change in isotope ratios, protein abundance levels and protein synthesis, degradation and turnover rates were calculated for the whole cell and for the respective cytoplasmic, nuclear, and nucleolar compartments. Expression levels of endogenous HeLa proteins varied by up to seven orders of magnitude. The average turnover rate for HeLa proteins was ∼20 h. Turnover rate did not correlate with either molecular weight or net charge, but did correlate with abundance, with highly abundant proteins showing longer than average half-lives. Fast turnover proteins had overall a higher frequency of PEST motifs than slow turnover proteins but no general correlation was observed between amino or carboxyl terminal amino acid identities and turnover rates. A subset of proteins was identified that exist in pools with different turnover rates depending on their subcellular localization. This strongly correlated with subunits of large, multiprotein complexes, suggesting a general mechanism whereby their assembly is controlled in a different subcellular location to their main site of function. PMID:21937730

Deciphering the functions of O-GlcNAc glycosylation in the brain: The role of site-specific quantitative O-GlcNAcomics.

PubMed

Thompson, John W; Sorum, Alexander W; Hsieh-Wilson, Linda C

2018-06-23

The dynamic posttranslational modification O-linked β-N-acetylglucosamine glycosylation (O-GlcNAcylation) is present on thousands of intracellular proteins in the brain. Like phosphorylation, O-GlcNAcylation is inducible and plays important functional roles in both physiology and disease. Recent advances in mass spectrometry (MS) and bioconjugation methods are now enabling the mapping of O-GlcNAcylation events to individual sites in proteins. However, our understanding of which glycosylation events are necessary for regulating protein function and controlling specific processes, phenotypes, or diseases remains in its infancy. Given the sheer number of O-GlcNAc sites, methods are greatly needed to identify promising sites and prioritize them for time- and resource-intensive functional studies. Revealing sites that are dynamically altered by different stimuli or disease states will likely to go a long way in this regard. Here, we describe advanced methods for identifying O-GlcNAc sites on individual proteins and across the proteome, and for determining their stoichiometry in vivo. We also highlight emerging technologies for quantitative, site-specific MS-based O-GlcNAc proteomics (O-GlcNAcomics), which allow proteome-wide tracking of O-GlcNAcylation dynamics at individual sites. These cutting-edge technologies are beginning to bridge the gap between the high-throughput cataloging of O-GlcNAcylated proteins and the relatively low-throughput study of individual proteins. By uncovering the O-GlcNAcylation events that change in specific physiological and disease contexts, these new approaches are providing key insights into the regulatory functions of O-GlcNAc in the brain, including their roles in neuroprotection, neuronal signaling, learning and memory, and neurodegenerative diseases.

A General Method for Targeted Quantitative Cross-Linking Mass Spectrometry.

PubMed

Chavez, Juan D; Eng, Jimmy K; Schweppe, Devin K; Cilia, Michelle; Rivera, Keith; Zhong, Xuefei; Wu, Xia; Allen, Terrence; Khurgel, Moshe; Kumar, Akhilesh; Lampropoulos, Athanasios; Larsson, Mårten; Maity, Shuvadeep; Morozov, Yaroslav; Pathmasiri, Wimal; Perez-Neut, Mathew; Pineyro-Ruiz, Coriness; Polina, Elizabeth; Post, Stephanie; Rider, Mark; Tokmina-Roszyk, Dorota; Tyson, Katherine; Vieira Parrine Sant'Ana, Debora; Bruce, James E

2016-01-01

Chemical cross-linking mass spectrometry (XL-MS) provides protein structural information by identifying covalently linked proximal amino acid residues on protein surfaces. The information gained by this technique is complementary to other structural biology methods such as x-ray crystallography, NMR and cryo-electron microscopy[1]. The extension of traditional quantitative proteomics methods with chemical cross-linking can provide information on the structural dynamics of protein structures and protein complexes. The identification and quantitation of cross-linked peptides remains challenging for the general community, requiring specialized expertise ultimately limiting more widespread adoption of the technique. We describe a general method for targeted quantitative mass spectrometric analysis of cross-linked peptide pairs. We report the adaptation of the widely used, open source software package Skyline, for the analysis of quantitative XL-MS data as a means for data analysis and sharing of methods. We demonstrate the utility and robustness of the method with a cross-laboratory study and present data that is supported by and validates previously published data on quantified cross-linked peptide pairs. This advance provides an easy to use resource so that any lab with access to a LC-MS system capable of performing targeted quantitative analysis can quickly and accurately measure dynamic changes in protein structure and protein interactions.

Plasma proteins in the acquired denture pellicle enhance substrate surface free energy and Candida albicans phospholipase and proteinase activities.

PubMed

Custodio, William; Silva, Wander J; Paes Leme, Adriana F; Cury, Jaime A; Del Bel Cury, Altair A

2015-11-01

The objective of the present study was to determine if blood plasma proteins could change the proteome of the acquired denture pellicle by label-free quantitative proteomics. As pellicle proteome modulates the interaction between substrates and Candida cells, we investigated its effect on the surface free energy (SFE) of the coated resin and on Candida albicans phospholipase and aspartyl proteinase activities. Poly(methylmethacrylate) discs were exposed to saliva (control) or saliva enriched with blood plasma (experimental group). The pellicle proteome was analyzed by mass spectrometry coupled with liquid chromatography. SFE was determined by acid-base technique. After biofilm formation, phospholipase and proteinase activities were determined accordingly to classic plate methods. Data were analyzed by two-way anova and Tukey test (P < 0.05). α-Amylase, cystatins, mucins, and host-immune system proteins were the main proteins identified in the control group. Fibrinogen and albumin were observed only in the experimental group. Coated discs of the experimental group presented an increased SFE (P < 0.05). For both enzymes tested, the experimental group showed higher proteolytic activity (P < 0.001). Blood plasma changes the proteome of the acquired denture pellicle, increasing surface free energy and the activity of Candida albicans phospholipase and aspartyl proteinase. © 2014 Wiley Publishing Asia Pty Ltd.

Study of quantitative changes of cereal allergenic proteins after food processing.

PubMed

Flodrová, Dana; Benkovská, Dagmar; Laštovičková, Markéta

2015-03-30

Within last few years, the occurrence of food allergens and corresponding food allergies has been increasing, therefore research into the individual allergens is required. In the present work, the effect of cereal processing on the amounts of allergenic proteins is studied by modern proteomic-based approaches. The most important wheat and barley allergens are low-molecular-weight (LMW) proteins. Therefore we investigated the relative quantitative changes of these proteins after food technological processing, namely wheat couscous production and barley malting. A comparative study using mass spectrometry in connection with the technique of isobaric tag for relative and absolute quantification (iTRAQ) revealed that the amount of wheat allergenic LMW proteins decreased significantly during couscous production (approximately to 5-26% of their initial content in wheat flour). After barley malting, the amounts of the majority of LMW proteins decreased as well, although to a lesser extent than in the case of wheat/couscous. The level of two allergens even slightly increased. Suggested proteomic strategy proved as universal and sensitive method for fast and reliable identification of various cereal allergens and monitoring of their quantitative changes during food processing. Such information is important for consumers who suffer from allergies. © 2014 Society of Chemical Industry.

Development of an Efficient Protein Extraction Method Compatible with LC-MS/MS for Proteome Mapping in Two Australian Seagrasses Zostera muelleri and Posidonia australis

PubMed Central

Jiang, Zhijian; Kumar, Manoj; Padula, Matthew P.; Pernice, Mathieu; Kahlke, Tim; Kim, Mikael; Ralph, Peter J.

2017-01-01

The availability of the first complete genome sequence of the marine flowering plant Zostera marina (commonly known as seagrass) in early 2016, is expected to significantly raise the impact of seagrass proteomics. Seagrasses are marine ecosystem engineers that are currently declining worldwide at an alarming rate due to both natural and anthropogenic disturbances. Seagrasses (especially species of the genus Zostera) are compromised for proteomic studies primarily due to the lack of efficient protein extraction methods because of their recalcitrant cell wall which is rich in complex polysaccharides and a high abundance of secondary metabolites in their cells. In the present study, three protein extraction methods that are commonly used in plant proteomics i.e., phenol (P); trichloroacetic acid/acetone/SDS/phenol (TASP); and borax/polyvinyl-polypyrrolidone/phenol (BPP) extraction, were evaluated quantitatively and qualitatively based on two dimensional isoelectric focusing (2D-IEF) maps and LC-MS/MS analysis using the two most abundant Australian seagrass species, namely Zostera muelleri and Posidonia australis. All three tested methods produced high quality protein extracts with excellent 2D-IEF maps in P. australis. However, the BPP method produces better results in Z. muelleri compared to TASP and P. Therefore, we further modified the BPP method (M-BPP) by homogenizing the tissue in a modified protein extraction buffer containing both ionic and non-ionic detergents (0.5% SDS; 1.5% Triton X-100), 2% PVPP and protease inhibitors. Further, the extracted proteins were solubilized in 0.5% of zwitterionic detergent (C7BzO) instead of 4% CHAPS. This slight modification to the BPP method resulted in a higher protein yield, and good quality 2-DE maps with a higher number of protein spots in both the tested seagrasses. Further, the M-BPP method was successfully utilized in western-blot analysis of phosphoenolpyruvate carboxylase (PEPC—a key enzyme for carbon metabolism). This optimized protein extraction method will be a significant stride toward seagrass proteome mining and identifying the protein biomarkers to stress response of seagrasses under the scenario of global climate change and anthropogenic perturbations. PMID:28861098

Development of an Efficient Protein Extraction Method Compatible with LC-MS/MS for Proteome Mapping in Two Australian Seagrasses Zostera muelleri and Posidonia australis.

PubMed

Jiang, Zhijian; Kumar, Manoj; Padula, Matthew P; Pernice, Mathieu; Kahlke, Tim; Kim, Mikael; Ralph, Peter J

2017-01-01

The availability of the first complete genome sequence of the marine flowering plant Zostera marina (commonly known as seagrass) in early 2016, is expected to significantly raise the impact of seagrass proteomics. Seagrasses are marine ecosystem engineers that are currently declining worldwide at an alarming rate due to both natural and anthropogenic disturbances. Seagrasses (especially species of the genus Zostera ) are compromised for proteomic studies primarily due to the lack of efficient protein extraction methods because of their recalcitrant cell wall which is rich in complex polysaccharides and a high abundance of secondary metabolites in their cells. In the present study, three protein extraction methods that are commonly used in plant proteomics i.e., phenol (P); trichloroacetic acid/acetone/SDS/phenol (TASP); and borax/polyvinyl-polypyrrolidone/phenol (BPP) extraction, were evaluated quantitatively and qualitatively based on two dimensional isoelectric focusing (2D-IEF) maps and LC-MS/MS analysis using the two most abundant Australian seagrass species, namely Zostera muelleri and Posidonia australis . All three tested methods produced high quality protein extracts with excellent 2D-IEF maps in P. australis . However, the BPP method produces better results in Z. muelleri compared to TASP and P. Therefore, we further modified the BPP method (M-BPP) by homogenizing the tissue in a modified protein extraction buffer containing both ionic and non-ionic detergents (0.5% SDS; 1.5% Triton X-100), 2% PVPP and protease inhibitors. Further, the extracted proteins were solubilized in 0.5% of zwitterionic detergent (C7BzO) instead of 4% CHAPS. This slight modification to the BPP method resulted in a higher protein yield, and good quality 2-DE maps with a higher number of protein spots in both the tested seagrasses. Further, the M-BPP method was successfully utilized in western-blot analysis of phosphoenolpyruvate carboxylase (PEPC-a key enzyme for carbon metabolism). This optimized protein extraction method will be a significant stride toward seagrass proteome mining and identifying the protein biomarkers to stress response of seagrasses under the scenario of global climate change and anthropogenic perturbations.

A comparative analysis of human plasma and serum proteins by combining native PAGE, whole-gel slicing and quantitative LC-MS/MS: Utilizing native MS-electropherograms in proteomic analysis for discovering structure and interaction-correlated differences.

PubMed

Wen, Meiling; Jin, Ya; Manabe, Takashi; Chen, Shumin; Tan, Wen

2017-12-01

MS identification has long been used for PAGE-separated protein bands, but global and systematic quantitation utilizing MS after PAGE has remained rare and not been reported for native PAGE. Here we reported on a new method combining native PAGE, whole-gel slicing and quantitative LC-MS/MS, aiming at comparative analysis on not only abundance, but also structures and interactions of proteins. A pair of human plasma and serum samples were used as test samples and separated on a native PAGE gel. Six lanes of each sample were cut, each lane was further sliced into thirty-five 1.1 mm × 1.1 mm squares and all the squares were subjected to standardized procedures of in-gel digestion and quantitative LC-MS/MS. The results comprised 958 data rows that each contained abundance values of a protein detected in one square in eleven gel lanes (one plasma lane excluded). The data were evaluated to have satisfactory reproducibility of assignment and quantitation. Totally 315 proteins were assigned, with each protein assigned in 1-28 squares. The abundance distributions in the plasma and serum gel lanes were reconstructed for each protein, named as "native MS-electropherograms". Comparison of the electropherograms revealed significant plasma-versus-serum differences on 33 proteins in 87 squares (fold difference > 2 or < 0.5, p < 0.05). Many of the differences matched with accumulated knowledge on protein interactions and proteolysis involved in blood coagulation, complement and wound healing processes. We expect this method would be useful to provide more comprehensive information in comparative proteomic analysis, on both quantities and structures/interactions. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

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

PubMed

Zauber, Henrik; Schulze, Waltraud X

2012-11-02

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

Differential expression profiling of serum proteins and metabolites for biomarker discovery

NASA Astrophysics Data System (ADS)

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

2004-11-01

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

IDAWG: Metabolic incorporation of stable isotope labels for quantitative glycomics of cultured cells

PubMed Central

Orlando, Ron; Lim, Jae-Min; Atwood, James A.; Angel, Peggi M.; Fang, Meng; Aoki, Kazuhiro; Alvarez-Manilla, Gerardo; Moremen, Kelley W.; York, William S.; Tiemeyer, Michael; Pierce, Michael; Dalton, Stephen; Wells, Lance

2012-01-01

Robust quantification is an essential component of comparative –omic strategies. In this regard, glycomics lags behind proteomics. Although various isotope-tagging and direct quantification methods have recently enhanced comparative glycan analysis, a cell culture labeling strategy, that could provide for glycomics the advantages that SILAC provides for proteomics, has not been described. Here we report the development of IDAWG, Isotopic Detection of Aminosugars With Glutamine, for the incorporation of differential mass tags into the glycans of cultured cells. In this method, culture media containing amide-15N-Gln is used to metabolically label cellular aminosugars with heavy nitrogen. Because the amide side chain of Gln is the sole source of nitrogen for the biosynthesis of GlcNAc, GalNAc, and sialic acid, we demonstrate that culturing mouse embryonic stems cells for 72 hours in the presence of amide-15N-Gln media results in nearly complete incorporation of 15N into N-linked and O-linked glycans. The isotopically heavy monosaccharide residues provide additional information for interpreting glycan fragmentation and also allow quantification in both full MS and MS/MS modes. Thus, IDAWG is a simple to implement, yet powerful quantitative tool for the glycomics toolbox. PMID:19449840

Quantitative Analysis of Energy Metabolic Pathways in MCF-7 Breast Cancer Cells by Selected Reaction Monitoring Assay*

PubMed Central

Drabovich, Andrei P.; Pavlou, Maria P.; Dimitromanolakis, Apostolos; Diamandis, Eleftherios P.

2012-01-01

To investigate the quantitative response of energy metabolic pathways in human MCF-7 breast cancer cells to hypoxia, glucose deprivation, and estradiol stimulation, we developed a targeted proteomics assay for accurate quantification of protein expression in glycolysis/gluconeogenesis, TCA cycle, and pentose phosphate pathways. Cell growth conditions were selected to roughly mimic the exposure of cells in the cancer tissue to the intermittent hypoxia, glucose deprivation, and hormonal stimulation. Targeted proteomics assay allowed for reproducible quantification of 76 proteins in four different growth conditions after 24 and 48 h of perturbation. Differential expression of a number of control and metabolic pathway proteins in response to the change of growth conditions was found. Elevated expression of the majority of glycolytic enzymes was observed in hypoxia. Cancer cells, as opposed to near-normal MCF-10A cells, exhibited significantly increased expression of key energy metabolic pathway enzymes (FBP1, IDH2, and G6PD) that are known to redirect cellular metabolism and increase carbon flux through the pentose phosphate pathway. Our quantitative proteomic protocol is based on a mass spectrometry-compatible acid-labile detergent and is described in detail. Optimized parameters of a multiplex selected reaction monitoring (SRM) assay for 76 proteins, 134 proteotypic peptides, and 401 transitions are included and can be downloaded and used with any SRM-compatible mass spectrometer. The presented workflow is an integrated tool for hypothesis-driven studies of mammalian cells as well as functional studies of proteins, and can greatly complement experimental methods in systems biology, metabolic engineering, and metabolic transformation of cancer cells. PMID:22535206

Proteomic landscape in Central and Eastern Europe: the 9th Central and Eastern European Proteomic Conference, Poznań, Poland.

PubMed

Gadher, Suresh Jivan; Marczak, Łukasz; Łuczak, Magdalena; Stobiecki, Maciej; Widlak, Piotr; Kovarova, Hana

2016-01-01

Every year since 2007, the Central and Eastern European Proteomic Conference (CEEPC) has excelled in representing state-of-the-art proteomics in and around Central and Eastern Europe, and linking it to international institutions worldwide. Its mission remains to contribute to all approaches of proteomics including traditional and often-revisited methodologies as well as the latest technological achievements in clinical, quantitative and structural proteomics with a view to systems biology of a variety of processes. The 9th CEEPC was held from June 15th to 18th, 2015, at the Institute of Bioorganic Chemistry, Polish Academy of Sciences in Poznań, Poland. The scientific program stimulated exchange of proteomic knowledge whilst the spectacular venue of the conference allowed participants to enjoy the cobblestoned historical city of Poznań.

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

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

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

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

Development of data representation standards by the human proteome organization proteomics standards initiative

PubMed Central

Albar, Juan Pablo; Binz, Pierre-Alain; Eisenacher, Martin; Jones, Andrew R; Mayer, Gerhard; Omenn, Gilbert S; Orchard, Sandra; Vizcaíno, Juan Antonio; Hermjakob, Henning

2015-01-01

Objective To describe the goals of the Proteomics Standards Initiative (PSI) of the Human Proteome Organization, the methods that the PSI has employed to create data standards, the resulting output of the PSI, lessons learned from the PSI’s evolution, and future directions and synergies for the group. Materials and Methods The PSI has 5 categories of deliverables that have guided the group. These are minimum information guidelines, data formats, controlled vocabularies, resources and software tools, and dissemination activities. These deliverables are produced via the leadership and working group organization of the initiative, driven by frequent workshops and ongoing communication within the working groups. Official standards are subjected to a rigorous document process that includes several levels of peer review prior to release. Results We have produced and published minimum information guidelines describing what information should be provided when making data public, either via public repositories or other means. The PSI has produced a series of standard formats covering mass spectrometer input, mass spectrometer output, results of informatics analysis (both qualitative and quantitative analyses), reports of molecular interaction data, and gel electrophoresis analyses. We have produced controlled vocabularies that ensure that concepts are uniformly annotated in the formats and engaged in extensive software development and dissemination efforts so that the standards can efficiently be used by the community. Conclusion In its first dozen years of operation, the PSI has produced many standards that have accelerated the field of proteomics by facilitating data exchange and deposition to data repositories. We look to the future to continue developing standards for new proteomics technologies and workflows and mechanisms for integration with other omics data types. Our products facilitate the translation of genomics and proteomics findings to clinical and biological phenotypes. The PSI website can be accessed at http://www.psidev.info. PMID:25726569

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

PubMed Central

Sobrero, Patricio; Schlüter, Jan-Philip; Lanner, Ulrike; Schlosser, Andreas; Becker, Anke; Valverde, Claudio

2012-01-01

Riboregulation stands for RNA-based control of gene expression. In bacteria, small non-coding RNAs (sRNAs) are a major class of riboregulatory elements, most of which act at the post-transcriptional level by base-pairing target mRNA genes. The RNA chaperone Hfq facilitates antisense interactions between target mRNAs and regulatory sRNAs, thus influencing mRNA stability and/or translation rate. In the α-proteobacterium Sinorhizobium meliloti strain 2011, the identification and detection of multiple sRNAs genes and the broadly pleitropic phenotype associated to the absence of a functional Hfq protein both support the existence of riboregulatory circuits controlling gene expression to ensure the fitness of this bacterium in both free living and symbiotic conditions. In order to identify target mRNAs subject to Hfq-dependent riboregulation, we have compared the proteome of an hfq mutant and the wild type S. meliloti by quantitative proteomics following protein labelling with 15N. Among 2139 univocally identified proteins, a total of 195 proteins showed a differential abundance between the Hfq mutant and the wild type strain; 65 proteins accumulated ≥2-fold whereas 130 were downregulated (≤0.5-fold) in the absence of Hfq. This profound proteomic impact implies a major role for Hfq on regulation of diverse physiological processes in S. meliloti, from transport of small molecules to homeostasis of iron and nitrogen. Changes in the cellular levels of proteins involved in transport of nucleotides, peptides and amino acids, and in iron homeostasis, were confirmed with phenotypic assays. These results represent the first quantitative proteomic analysis in S. meliloti. The comparative analysis of the hfq mutant proteome allowed identification of novel strongly Hfq-regulated genes in S. meliloti. PMID:23119037

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

PubMed

Sobrero, Patricio; Schlüter, Jan-Philip; Lanner, Ulrike; Schlosser, Andreas; Becker, Anke; Valverde, Claudio

2012-01-01

Riboregulation stands for RNA-based control of gene expression. In bacteria, small non-coding RNAs (sRNAs) are a major class of riboregulatory elements, most of which act at the post-transcriptional level by base-pairing target mRNA genes. The RNA chaperone Hfq facilitates antisense interactions between target mRNAs and regulatory sRNAs, thus influencing mRNA stability and/or translation rate. In the α-proteobacterium Sinorhizobium meliloti strain 2011, the identification and detection of multiple sRNAs genes and the broadly pleitropic phenotype associated to the absence of a functional Hfq protein both support the existence of riboregulatory circuits controlling gene expression to ensure the fitness of this bacterium in both free living and symbiotic conditions. In order to identify target mRNAs subject to Hfq-dependent riboregulation, we have compared the proteome of an hfq mutant and the wild type S. meliloti by quantitative proteomics following protein labelling with (15)N. Among 2139 univocally identified proteins, a total of 195 proteins showed a differential abundance between the Hfq mutant and the wild type strain; 65 proteins accumulated ≥2-fold whereas 130 were downregulated (≤0.5-fold) in the absence of Hfq. This profound proteomic impact implies a major role for Hfq on regulation of diverse physiological processes in S. meliloti, from transport of small molecules to homeostasis of iron and nitrogen. Changes in the cellular levels of proteins involved in transport of nucleotides, peptides and amino acids, and in iron homeostasis, were confirmed with phenotypic assays. These results represent the first quantitative proteomic analysis in S. meliloti. The comparative analysis of the hfq mutant proteome allowed identification of novel strongly Hfq-regulated genes in S. meliloti.

The developmental proteome of Drosophila melanogaster

PubMed Central

Casas-Vila, Nuria; Bluhm, Alina; Sayols, Sergi; Dinges, Nadja; Dejung, Mario; Altenhein, Tina; Kappei, Dennis; Altenhein, Benjamin; Roignant, Jean-Yves; Butter, Falk

2017-01-01

Drosophila melanogaster is a widely used genetic model organism in developmental biology. While this model organism has been intensively studied at the RNA level, a comprehensive proteomic study covering the complete life cycle is still missing. Here, we apply label-free quantitative proteomics to explore proteome remodeling across Drosophila’s life cycle, resulting in 7952 proteins, and provide a high temporal-resolved embryogenesis proteome of 5458 proteins. Our proteome data enabled us to monitor isoform-specific expression of 34 genes during development, to identify the pseudogene Cyp9f3Ψ as a protein-coding gene, and to obtain evidence of 268 small proteins. Moreover, the comparison with available transcriptomic data uncovered examples of poor correlation between mRNA and protein, underscoring the importance of proteomics to study developmental progression. Data integration of our embryogenesis proteome with tissue-specific data revealed spatial and temporal information for further functional studies of yet uncharacterized proteins. Overall, our high resolution proteomes provide a powerful resource and can be explored in detail in our interactive web interface. PMID:28381612

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.

Skyline: an open source document editor for creating and analyzing targeted proteomics experiments.

PubMed

MacLean, Brendan; Tomazela, Daniela M; Shulman, Nicholas; Chambers, Matthew; Finney, Gregory L; Frewen, Barbara; Kern, Randall; Tabb, David L; Liebler, Daniel C; MacCoss, Michael J

2010-04-01

Skyline is a Windows client application for targeted proteomics method creation and quantitative data analysis. It is open source and freely available for academic and commercial use. The Skyline user interface simplifies the development of mass spectrometer methods and the analysis of data from targeted proteomics experiments performed using selected reaction monitoring (SRM). Skyline supports using and creating MS/MS spectral libraries from a wide variety of sources to choose SRM filters and verify results based on previously observed ion trap data. Skyline exports transition lists to and imports the native output files from Agilent, Applied Biosystems, Thermo Fisher Scientific and Waters triple quadrupole instruments, seamlessly connecting mass spectrometer output back to the experimental design document. The fast and compact Skyline file format is easily shared, even for experiments requiring many sample injections. A rich array of graphs displays results and provides powerful tools for inspecting data integrity as data are acquired, helping instrument operators to identify problems early. The Skyline dynamic report designer exports tabular data from the Skyline document model for in-depth analysis with common statistical tools. Single-click, self-updating web installation is available at http://proteome.gs.washington.edu/software/skyline. This web site also provides access to instructional videos, a support board, an issues list and a link to the source code project.

Monitoring Peptidase Activities in Complex Proteomes by MALDI-TOF Mass Spectrometry

PubMed Central

Villanueva, Josep; Nazarian, Arpi; Lawlor, Kevin; Tempst, Paul

2009-01-01

Measuring enzymatic activities in biological fluids is a form of activity-based proteomics and may be utilized as a means of developing disease biomarkers. Activity-based assays allow amplification of output signals, thus potentially visualizing low-abundant enzymes on a virtually transparent whole-proteome background. The protocol presented here describes a semi-quantitative in vitro assay of proteolytic activities in complex proteomes by monitoring breakdown of designer peptide-substrates using robotic extraction and a MALDI-TOF mass spectrometric read-out. Relative quantitation of the peptide metabolites is done by comparison with spiked internal standards, followed by statistical analysis of the resulting mini-peptidome. Partial automation provides reproducibility and throughput essential for comparing large sample sets. The approach may be employed for diagnostic or predictive purposes and enables profiling of 96 samples in 30 hours. It could be tailored to many diagnostic and pharmaco-dynamic purposes, as a read-out of catalytic and metabolic activities in body fluids or tissues. PMID:19617888

Mapping the Extracellular and Membrane Proteome Associated with the Vasculature and the Stroma in the Embryo*

PubMed Central

Soulet, Fabienne; Kilarski, Witold W.; Roux-Dalvai, Florence; Herbert, John M. J.; Sacewicz, Izabela; Mouton-Barbosa, Emmanuelle; Bicknell, Roy; Lalor, Patricia; Monsarrat, Bernard; Bikfalvi, Andreas

2013-01-01

In order to map the extracellular or membrane proteome associated with the vasculature and the stroma in an embryonic organism in vivo, we developed a biotinylation technique for chicken embryo and combined it with mass spectrometry and bioinformatic analysis. We also applied this procedure to implanted tumors growing on the chorioallantoic membrane or after the induction of granulation tissue. Membrane and extracellular matrix proteins were the most abundant components identified. Relative quantitative analysis revealed differential protein expression patterns in several tissues. Through a bioinformatic approach, we determined endothelial cell protein expression signatures, which allowed us to identify several proteins not yet reported to be associated with endothelial cells or the vasculature. This is the first study reported so far that applies in vivo biotinylation, in combination with robust label-free quantitative proteomics approaches and bioinformatic analysis, to an embryonic organism. It also provides the first description of the vascular and matrix proteome of the embryo that might constitute the starting point for further developments. PMID:23674615

Isobaric Tags for Relative and Absolute Quantitation-Based Proteomic Analysis of Patent and Constricted Ductus Arteriosus Tissues Confirms the Systemic Regulation of Ductus Arteriosus Closure.

PubMed

Hong, Haifa; Ye, Lincai; Chen, Huiwen; Xia, Yu; Liu, Yue; Liu, Jinfen; Lu, Yanan; Zhang, Haibo

2015-08-01

We aimed to evaluate global changes in protein expression associated with patency by undertaking proteomic analysis of human constricted and patent ductus arteriosus (DA). Ten constricted and 10 patent human DAs were excised from infants with ductal-dependent heart disease during surgery. Using isobaric tags for relative and absolute quantitation-based quantitative proteomics, 132 differentially expressed proteins were identified. Of 132 proteins, voltage-gated sodium channel 1.3 (SCN3A), myosin 1d (Myo1d), Rho GTPase activating protein 26 (ARHGAP26), and retinitis pigmentosa 1 (RP1) were selected for validation by Western blot and quantitative real-time polymerase chain reaction analyses. Significant upregulation of SCN3A, Myo1d, and RP1 messenger RNA, and protein levels was observed in the patent DA group (all P ≤ 0.048). ARHGAP26 messenger RNA and protein levels were decreased in patent DA tissue (both P ≤ 0.018). Immunohistochemistry analysis revealed that Myo1d, ARHGAP26, and RP1 were specifically expressed in the subendothelial region of constricted DAs; however, diffuse expression of these proteins was noted in the patent group. Proteomic analysis revealed global changes in the expression of proteins that regulate oxygen sensing, ion channels, smooth muscle cell migration, nervous system, immune system, and metabolism, suggesting a basis for the systemic regulation of DA patency by diverse signaling pathways, which will be confirmed in further studies.

Quantitative proteomic analysis of paired colorectal cancer and non-tumorigenic tissues reveals signature proteins and perturbed pathways involved in CRC progression and metastasis.

PubMed

Sethi, Manveen K; Thaysen-Andersen, Morten; Kim, Hoguen; Park, Cheol Keun; Baker, Mark S; Packer, Nicolle H; Paik, Young-Ki; Hancock, William S; Fanayan, Susan

2015-08-03

Modern proteomics has proven instrumental in our understanding of the molecular deregulations associated with the development and progression of cancer. Herein, we profile membrane-enriched proteome of tumor and adjacent normal tissues from eight CRC patients using label-free nanoLC-MS/MS-based quantitative proteomics and advanced pathway analysis. Of the 948 identified proteins, 184 proteins were differentially expressed (P<0.05, fold change>1.5) between the tumor and non-tumor tissue (69 up-regulated and 115 down-regulated in tumor tissues). The CRC tumor and non-tumor tissues clustered tightly in separate groups using hierarchical cluster analysis of the differentially expressed proteins, indicating a strong CRC-association of this proteome subset. Specifically, cancer associated proteins such as FN1, TNC, DEFA1, ITGB2, MLEC, CDH17, EZR and pathways including actin cytoskeleton and RhoGDI signaling were deregulated. Stage-specific proteome signatures were identified including up-regulated ribosomal proteins and down-regulated annexin proteins in early stage CRC. Finally, EGFR(+) CRC tissues showed an EGFR-dependent down-regulation of cell adhesion molecules, relative to EGFR(-) tissues. Taken together, this study provides a detailed map of the altered proteome and associated protein pathways in CRC, which enhances our mechanistic understanding of CRC biology and opens avenues for a knowledge-driven search for candidate CRC protein markers. Copyright © 2015 Elsevier B.V. All rights reserved.

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

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

GO Explorer: A gene-ontology tool to aid in the interpretation of shotgun proteomics data.

PubMed

Carvalho, Paulo C; Fischer, Juliana Sg; Chen, Emily I; Domont, Gilberto B; Carvalho, Maria Gc; Degrave, Wim M; Yates, John R; Barbosa, Valmir C

2009-02-24

Spectral counting is a shotgun proteomics approach comprising the identification and relative quantitation of thousands of proteins in complex mixtures. However, this strategy generates bewildering amounts of data whose biological interpretation is a challenge. Here we present a new algorithm, termed GO Explorer (GOEx), that leverages the gene ontology (GO) to aid in the interpretation of proteomic data. GOEx stands out because it combines data from protein fold changes with GO over-representation statistics to help draw conclusions. Moreover, it is tightly integrated within the PatternLab for Proteomics project and, thus, lies within a complete computational environment that provides parsers and pattern recognition tools designed for spectral counting. GOEx offers three independent methods to query data: an interactive directed acyclic graph, a specialist mode where key words can be searched, and an automatic search. Its usefulness is demonstrated by applying it to help interpret the effects of perillyl alcohol, a natural chemotherapeutic agent, on glioblastoma multiform cell lines (A172). We used a new multi-surfactant shotgun proteomic strategy and identified more than 2600 proteins; GOEx pinpointed key sets of differentially expressed proteins related to cell cycle, alcohol catabolism, the Ras pathway, apoptosis, and stress response, to name a few. GOEx facilitates organism-specific studies by leveraging GO and providing a rich graphical user interface. It is a simple to use tool, specialized for biologists who wish to analyze spectral counting data from shotgun proteomics. GOEx is available at http://pcarvalho.com/patternlab.

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

PubMed

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

2018-06-21

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

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

PubMed

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

2016-10-07

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

Proteomic analysis of mitochondria in respiratory epithelial cells infected with human respiratory syncytial virus and functional implications for virus and cell biology.

PubMed

Munday, Diane C; Howell, Gareth; Barr, John N; Hiscox, Julian A

2015-03-01

The aim of this study was to quantitatively characterise the mitochondrial proteome of airway epithelial cells infected with human respiratory syncytial virus (HRSV), a major cause of paediatric illness. Quantitative proteomics, underpinned by stable isotope labelling with amino acids in cell culture, coupled to LC-MS/MS, was applied to mitochondrial fractions prepared from HRSV-infected and mock-infected cells 12 and 24 h post-infection. Datasets were analysed using ingenuity pathway analysis, and the results were validated and characterised using bioimaging, targeted inhibition and gene depletion. The data quantitatively indicated that antiviral signalling proteins converged on mitochondria during HRSV infection. The mitochondrial receptor protein Tom70 was found to act in an antiviral manner, while its chaperone, Hsp90, was confirmed to be a positive viral factor. Proteins associated with different organelles were also co-enriched in the mitochondrial fractions from HRSV-infected cells, suggesting that alterations in organelle dynamics and membrane associations occur during virus infection. Protein and pathway-specific alterations occur to the mitochondrial proteome in a spatial and temporal manner during HRSV infection, suggesting that this organelle may have altered functions. These could be targeted as part of potential therapeutic strategies to disrupt virus biology. © 2014 Royal Pharmaceutical Society.

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.

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

PubMed

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

2008-02-01

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

Integrating cell biology and proteomic approaches in plants.

PubMed

Takáč, Tomáš; Šamajová, Olga; Šamaj, Jozef

2017-10-03

Significant improvements of protein extraction, separation, mass spectrometry and bioinformatics nurtured advancements of proteomics during the past years. The usefulness of proteomics in the investigation of biological problems can be enhanced by integration with other experimental methods from cell biology, genetics, biochemistry, pharmacology, molecular biology and other omics approaches including transcriptomics and metabolomics. This review aims to summarize current trends integrating cell biology and proteomics in plant science. Cell biology approaches are most frequently used in proteomic studies investigating subcellular and developmental proteomes, however, they were also employed in proteomic studies exploring abiotic and biotic stress responses, vesicular transport, cytoskeleton and protein posttranslational modifications. They are used either for detailed cellular or ultrastructural characterization of the object subjected to proteomic study, validation of proteomic results or to expand proteomic data. In this respect, a broad spectrum of methods is employed to support proteomic studies including ultrastructural electron microscopy studies, histochemical staining, immunochemical localization, in vivo imaging of fluorescently tagged proteins and visualization of protein-protein interactions. Thus, cell biological observations on fixed or living cell compartments, cells, tissues and organs are feasible, and in some cases fundamental for the validation and complementation of proteomic data. Validation of proteomic data by independent experimental methods requires development of new complementary approaches. Benefits of cell biology methods and techniques are not sufficiently highlighted in current proteomic studies. This encouraged us to review most popular cell biology methods used in proteomic studies and to evaluate their relevance and potential for proteomic data validation and enrichment of purely proteomic analyses. We also provide examples of representative studies combining proteomic and cell biology methods for various purposes. Integrating cell biology approaches with proteomic ones allow validation and better interpretation of proteomic data. Moreover, cell biology methods remarkably extend the knowledge provided by proteomic studies and might be fundamental for the functional complementation of proteomic data. This review article summarizes current literature linking proteomics with cell biology. Copyright © 2017 Elsevier B.V. All rights reserved.

Exploring the Spatial and Temporal Organization of a Cell’s Proteome

PubMed Central

Beck, Martin; Topf, Maya; Frazier, Zachary; Tjong, Harianto; Xu, Min; Zhang, Shihua; Alber, Frank

2013-01-01

To increase our current understanding of cellular processes, such as cell signaling and division, knowledge is needed about the spatial and temporal organization of the proteome at different organizational levels. These levels cover a wide range of length and time scales: from the atomic structures of macromolecules for inferring their molecular function, to the quantitative description of their abundance, and distribution in the cell. Emerging new experimental technologies are greatly increasing the availability of such spatial information on the molecular organization in living cells. This review addresses three fields that have significantly contributed to our understanding of the proteome’s spatial and temporal organization: first, methods for the structure determination of individual macromolecular assemblies, specifically the fitting of atomic structures into density maps generated from electron microscopy techniques; second, research that visualizes the spatial distributions of these complexes within the cellular context using cryo electron tomography techniques combined with computational image processing; and third, methods for the spatial modeling of the dynamic organization of the proteome, specifically those methods for simulating reaction and diffusion of proteins and complexes in crowded intracellular fluids. The long-term goal is to integrate the varied data about a proteome’s organization into a spatially explicit, predictive model of cellular processes. PMID:21094684

A proteomic approach reveals the variation in human platelet protein composition after storage at different temperatures.

PubMed

Wang, Shichun; Jiang, Tianlun; Fan, Yahan; Zhao, Shuming

2018-03-29

Cryopreservation can slow down the metabolism and decrease the risk of bacterial contamination. But, chilled platelets (PLTs) show a reduced period in circulation due to the rapid clearance by hepatic cells or spleen macrophages after transfusion. The deleterious changes that PLTs undergo are mainly considered the result of PLT protein variation. However, the basis for proteomic variation of stored PLTs remains poorly understood. Besides count, activation markers (CD62P and Annexin V), and aggregation, we used quantitative mass spectrometry to create the first comprehensive and quantitative human PLT proteome of samples stored at different temperatures (22°C, 10°C and -80°C). We found different conditions caused different platelet storage lesion (PSL). PLT count was decreased no matter at what temperature stored. PLTs viability at low temperature dropped by 21.78% and 11.21%, respectively, as compared 10.26% at room temperature, there were no significant differences between the storage methods. Membrane expression of CD62P gradually increased in all groups especially stored at 22°C up to 40% and 10°C up to 30%. However, exposure of PS on the PLT membrane was below 1% in every group. The PLT proteome showed there were 575 and 454 potential proteins identified by general iTRAQ analysis and phosphorylation iTRAQ a nalysis, respectively, among them, 33 common differentially expressed proteins caused by storage time and 44 caused by storage temperature Especially, membrane-bound proteins (such as FERMT3, STX4, MYL9 and TAGLN2) played key roles in PLT storage lesion. The pathways "Endocytosis", "Fc gamma R-mediated phagocytosis" and "Regulation of actin cytoskeleton" were affected predominantly by storage time. And the pathways "SNARE interactions in vesicular transport" and "Vasopressin-regulated water reabsorption" were affected by cold storage in our study. Proteomic results can help us to understand PLT biochemistry and physiology and thus unravel the mechanisms of PSL in time and space for more successful PLT transfusion therapy.

Comparison between Procedures using Sodium Dodecyl Sulfate for Shotgun Proteomic Analyses of Complex Samples

PubMed Central

Bereman, Michael S.; Egertson, Jarrett D.; MacCoss, Michael J.

2012-01-01

Filter aided sample preparation (FASP) and a new sample preparation method using a modified commercial SDS removal spin column are quantitatively compared in terms of their performance for shotgun proteomic experiments in three complex proteomic samples: a Saccharomyces cerevisiae lysate (insoluble fraction), a Caenorhabditis elegans lysate (soluble fraction), and a human embryonic kidney cell line (HEK293T). The characteristics and total number of peptides and proteins identified are compared between the two procedures. The SDS spin column procedure affords a conservative 4-fold improvement in throughput, is more reproducible, less expensive (i.e., requires less materials), and identifies between 30–107% more peptides at a q≤0.01, than the FASP procedure. The peptides identified by SDS spin column are more hydrophobic than species identified by the FASP procedure as indicated by the distribution of GRAVY scores. Ultimately, these improvements correlate to as great as a 50% increase in protein identifications with 2 or more peptides. PMID:21656683

How may targeted proteomics complement genomic data in breast cancer?

PubMed

Guerin, Mathilde; Gonçalves, Anthony; Toiron, Yves; Baudelet, Emilie; Audebert, Stéphane; Boyer, Jean-Baptiste; Borg, Jean-Paul; Camoin, Luc

2017-01-01

Breast cancer (BC) is the most common female cancer in the world and was recently deconstructed in different molecular entities. Although most of the recent assays to characterize tumors at the molecular level are genomic-based, proteins are the actual executors of cellular functions and represent the vast majority of targets for anticancer drugs. Accumulated data has demonstrated an important level of quantitative and qualitative discrepancies between genomic/transcriptomic alterations and their protein counterparts, mostly related to the large number of post-translational modifications. Areas covered: This review will present novel proteomics technologies such as Reverse Phase Protein Array (RPPA) or mass-spectrometry (MS) based approaches that have emerged and that could progressively replace old-fashioned methods (e.g. immunohistochemistry, ELISA, etc.) to validate proteins as diagnostic, prognostic or predictive biomarkers, and eventually monitor them in the routine practice. Expert commentary: These different targeted proteomic approaches, able to complement genomic data in BC and characterize tumors more precisely, will permit to go through a more personalized treatment for each patient and tumor.

Proteomic data analysis of glioma cancer stem-cell lines based on novel nonlinear dimensional data reduction techniques

NASA Astrophysics Data System (ADS)

Lespinats, Sylvain; Pinker-Domenig, Katja; Wengert, Georg; Houben, Ivo; Lobbes, Marc; Stadlbauer, Andreas; Meyer-Bäse, Anke

2016-05-01

Glioma-derived cancer stem cells (GSCs) are tumor-initiating cells and may be refractory to radiation and chemotherapy and thus have important implications for tumor biology and therapeutics. The analysis and interpretation of large proteomic data sets requires the development of new data mining and visualization approaches. Traditional techniques are insufficient to interpret and visualize these resulting experimental data. The emphasis of this paper lies in the application of novel approaches for the visualization, clustering and projection representation to unveil hidden data structures relevant for the accurate interpretation of biological experiments. These qualitative and quantitative methods are applied to the proteomic analysis of data sets derived from the GSCs. The achieved clustering and visualization results provide a more detailed insight into the protein-level fold changes and putative upstream regulators for the GSCs. However the extracted molecular information is insufficient in classifying GSCs and paving the pathway to an improved therapeutics of the heterogeneous glioma.

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

PubMed

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

2011-07-01

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

Insights from quantitative metaproteomics and protein-stable isotope probing into microbial ecology.

PubMed

von Bergen, Martin; Jehmlich, Nico; Taubert, Martin; Vogt, Carsten; Bastida, Felipe; Herbst, Florian-Alexander; Schmidt, Frank; Richnow, Hans-Hermann; Seifert, Jana

2013-10-01

The recent development of metaproteomics has enabled the direct identification and quantification of expressed proteins from microbial communities in situ, without the need for microbial enrichment. This became possible by (1) significant increases in quality and quantity of metagenome data and by improvements of (2) accuracy and (3) sensitivity of modern mass spectrometers (MS). The identification of physiologically relevant enzymes can help to understand the role of specific species within a community or an ecological niche. Beside identification, relative and absolute quantitation is also crucial. We will review label-free and label-based methods of quantitation in MS-based proteome analysis and the contribution of quantitative proteome data to microbial ecology. Additionally, approaches of protein-based stable isotope probing (protein-SIP) for deciphering community structures are reviewed. Information on the species-specific metabolic activity can be obtained when substrates or nutrients are labeled with stable isotopes in a protein-SIP approach. The stable isotopes ((13)C, (15)N, (36)S) are incorporated into proteins and the rate of incorporation can be used for assessing the metabolic activity of the corresponding species. We will focus on the relevance of the metabolic and phylogenetic information retrieved with protein-SIP studies and for detecting and quantifying the carbon flux within microbial consortia. Furthermore, the combination of protein-SIP with established tools in microbial ecology such as other stable isotope probing techniques are discussed.

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

PubMed

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

2012-12-01

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

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

PubMed

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

2015-04-29

To elucidate the mechanisms contributing to fruit responses to senescence and stressful environmental stimuli under low temperature (LT) and controlled atmosphere (CA) storage, a label-free quantitative proteomic investigation was conducted in strawberry (Fragaria ananassa, Duch. cv. 'Akihime'). Postharvest physiological quality traits including firmness, total soluble solids, total acidity, ascorbic acid and volatile production were characterized following storage under different conditions. The observed post-storage protein expression profiles may be associated with delayed senescence features in strawberry. A total of 454 proteins were identified in differentially treated strawberry fruits. Quantitative analysis, using normalized spectral counts, revealed 73 proteins common to all treatments, which formed three clusters in a hierarchical clustering analysis. The proteins spanned a range of functions in various metabolic pathways and networks involved in carbohydrate and energy metabolism, volatile biosynthesis, phenylpropanoid activity, stress response and protein synthesis, degradation and folding. After CA and LT storage, 16 (13) and 11 (17) proteins, respectively, were significantly increased (decreased) in abundance, while expression profile of 12 proteins was significantly changed by both CA and LT. To summarize, the differential variability of abundance in strawberry proteome, working in a cooperative manner, provided an overview of the biological processes that occurred during CA and LT storage. Controlled atmosphere storage at an optimal temperature is regarded to be an effective postharvest technology to delay fruit senescence and maintain fruit quality during shelf life. Nonetheless, little information on fruit proteomic changes under controlled atmosphere and/or low temperature storage is available. The significance of this paper is that it is the first study employing a label-free approach in the investigation of strawberry fruit response to controlled atmosphere and cold storage. Changes in postharvest physiological quality traits including volatile production, firmness, ascorbic acid, soluble solids and total acidity were also characterized. Significant biological changes associated with senescence were revealed and differentially abundant proteins under various storage conditions were identified. Proteomic profiles were linked to physiological aspects of strawberry fruit senescence in order to provide new insights into possible regulation mechanisms. Findings from this study not only provide proteomic information on fruit regulation, but also pave the way for further quantitative studies at the transcriptomic and metabolomic levels. Copyright © 2015 Elsevier B.V. All rights reserved.

Analysis of disease-associated protein expression using quantitative proteomics—fibulin-5 is expressed in association with hepatic fibrosis.

PubMed

Bracht, Thilo; Schweinsberg, Vincent; Trippler, Martin; Kohl, Michael; Ahrens, Maike; Padden, Juliet; Naboulsi, Wael; Barkovits, Katalin; Megger, Dominik A; Eisenacher, Martin; Borchers, Christoph H; Schlaak, Jörg F; Hoffmann, Andreas-Claudius; Weber, Frank; Baba, Hideo A; Meyer, Helmut E; Sitek, Barbara

2015-05-01

Hepatic fibrosis and cirrhosis are major health problems worldwide. Until now, highly invasive biopsy remains the diagnostic gold standard despite many disadvantages. To develop noninvasive diagnostic assays for the assessment of liver fibrosis, it is urgently necessary to identify molecules that are robustly expressed in association with the disease. We analyzed biopsied tissue samples from 95 patients with HBV/HCV-associated hepatic fibrosis using three different quantification methods. We performed a label-free proteomics discovery study to identify novel disease-associated proteins using a subset of the cohort (n = 27). Subsequently, gene expression data from all available clinical samples were analyzed (n = 77). Finally, we performed a targeted proteomics approach, multiple reaction monitoring (MRM), to verify the disease-associated expression in samples independent from the discovery approach (n = 68). We identified fibulin-5 (FBLN5) as a novel protein expressed in relation to hepatic fibrosis. Furthermore, we confirmed the altered expression of microfibril-associated glycoprotein 4 (MFAP4), lumican (LUM), and collagen alpha-1(XIV) chain (COL14A1) in association to hepatic fibrosis. To our knowledge, no tissue-based quantitative proteomics study for hepatic fibrosis has been performed using a cohort of comparable size. By this means, we add substantial evidence for the disease-related expression of the proteins examined in this study.

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.

Identification of Mature Atherosclerotic Plaque Proteome Signatures Using Data-Independent Acquisition Mass Spectrometry.

PubMed

Hansmeier, Nicole; Buttigieg, Josef; Kumar, Pankaj; Pelle, Shaneen; Choi, Kyoo Yoon; Kopriva, David; Chao, Tzu-Chiao

2018-01-05

Atherosclerosis is a chronic inflammatory disease with complex pathobiology and one of the most common causes of cardiovascular events. The process is characterized by complex vascular remodeling processes that require the actions of numerous proteins. The composition of atherosclerotic plaque is increasingly recognized as a major factor governing the occurrence of cardiovascular or neurological symptoms. To gain deeper insights into the composition of atherosclerotic plaques, we created quantitative proteome profiles of advanced plaque tissues of six male patients undergoing carotid endarterectomy for stroke prevention. Using a quantitative, data-independent proteome approach, we identified 4181 proteins with an average protein coverage of 45%. An analysis of the quantitative composition of the tissue revealed key players of vascular remodeling processes. Moreover, compared with proximal arterial tissue, 20 proteins in mature plaques were enriched, whereas 52 proteins were found in lower quantities. Among the proteins with increased abundance were prominent extracellular matrix proteins such as biglycan and lumican, whereas cytoskeletal markers for contractile smooth muscle cells (SMCs) were decreased. Taken together, this study provides the most comprehensive quantitative assessment of mature human plaque tissue to date, which indicates a central role of SMCs in the structure of advanced atherosclerotic plaques.

Study of cellular oncometabolism via multidimensional protein identification technology.

PubMed

Aukim-Hastie, Claire; Garbis, Spiros D

2014-01-01

Cellular proteomics is becoming a widespread clinical application, matching the definition of bench-to-bedside translation. Among various fields of investigation, this approach can be applied to the study of the metabolic alterations that accompany oncogenesis and tumor progression, which are globally referred to as oncometabolism. Here, we describe a multidimensional protein identification technology (MuDPIT)-based strategy that can be employed to study the cellular proteome of malignant cells and tissues. This method has previously been shown to be compatible with the reproducible, in-depth analysis of up to a thousand proteins in clinical samples. The possibility to employ this technique to study clinical specimens demonstrates its robustness. MuDPIT is advantageous as compared to other approaches because it is direct, highly sensitive, and reproducible, it provides high resolution with ultra-high mass accuracy, it allows for relative quantifications, and it is compatible with multiplexing (thus limiting costs).This method enables the direct assessment of the proteomic profile of neoplastic cells and tissues and could be employed in the near future as a high-throughput, rapid, quantitative, and cost-effective screening platform for clinical samples. © 2014 Elsevier Inc. All rights reserved.

Quantitative and Comparative Profiling of Protease Substrates through a Genetically Encoded Multifunctional Photocrosslinker.

PubMed

He, Dan; Xie, Xiao; Yang, Fan; Zhang, Heng; Su, Haomiao; Ge, Yun; Song, Haiping; Chen, Peng R

2017-11-13

A genetically encoded, multifunctional photocrosslinker was developed for quantitative and comparative proteomics. By bearing a bioorthogonal handle and a releasable linker in addition to its photoaffinity warhead, this probe enables the enrichment of transient and low-abundance prey proteins after intracellular photocrosslinking and prey-bait separation, which can be subject to stable isotope dimethyl labeling and mass spectrometry analysis. This quantitative strategy (termed isoCAPP) allowed a comparative proteomic approach to be adopted to identify the proteolytic substrates of an E. coli protease-chaperone dual machinery DegP. Two newly identified substrates were subsequently confirmed by proteolysis experiments. © 2017 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

The future of targeted peptidomics.

PubMed

Findeisen, Peter

2013-12-01

Targeted MS is becoming increasingly important for sensitive and specific quantitative detection of proteins and respective PTMs. In this article, Ceglarek et al. [Proteomics Clin. Appl. 2013, 7, 794-801] present an LC-MS-based method for simultaneous quantitation of seven apolipoproteins in serum specimens. The assay fulfills many necessities of routine diagnostic applications, namely, low cost, high throughput, and good reproducibility. We anticipate that validation of new biomarkers will speed up with this technology and the palette of laboratory-based diagnostic tools will hopefully be augmented significantly in the near future. © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

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

PubMed

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

2013-04-05

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

A Comprehensive Guide for Performing Sample Preparation and Top-Down Protein Analysis

PubMed Central

Padula, Matthew P.; Berry, Iain J.; O′Rourke, Matthew B.; Raymond, Benjamin B.A.; Santos, Jerran; Djordjevic, Steven P.

2017-01-01

Methodologies for the global analysis of proteins in a sample, or proteome analysis, have been available since 1975 when Patrick O′Farrell published the first paper describing two-dimensional gel electrophoresis (2D-PAGE). This technique allowed the resolution of single protein isoforms, or proteoforms, into single ‘spots’ in a polyacrylamide gel, allowing the quantitation of changes in a proteoform′s abundance to ascertain changes in an organism′s phenotype when conditions change. In pursuit of the comprehensive profiling of the proteome, significant advances in technology have made the identification and quantitation of intact proteoforms from complex mixtures of proteins more routine, allowing analysis of the proteome from the ‘Top-Down’. However, the number of proteoforms detected by Top-Down methodologies such as 2D-PAGE or mass spectrometry has not significantly increased since O’Farrell’s paper when compared to Bottom-Up, peptide-centric techniques. This article explores and explains the numerous methodologies and technologies available to analyse the proteome from the Top-Down with a strong emphasis on the necessity to analyse intact proteoforms as a better indicator of changes in biology and phenotype. We arrive at the conclusion that the complete and comprehensive profiling of an organism′s proteome is still, at present, beyond our reach but the continuing evolution of protein fractionation techniques and mass spectrometry brings comprehensive Top-Down proteome profiling closer. PMID:28387712

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

PubMed Central

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

2013-01-01

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

A Comprehensive Guide for Performing Sample Preparation and Top-Down Protein Analysis.

PubMed

Padula, Matthew P; Berry, Iain J; O Rourke, Matthew B; Raymond, Benjamin B A; Santos, Jerran; Djordjevic, Steven P

2017-04-07

Methodologies for the global analysis of proteins in a sample, or proteome analysis, have been available since 1975 when Patrick O'Farrell published the first paper describing two-dimensional gel electrophoresis (2D-PAGE). This technique allowed the resolution of single protein isoforms, or proteoforms, into single 'spots' in a polyacrylamide gel, allowing the quantitation of changes in a proteoform's abundance to ascertain changes in an organism's phenotype when conditions change. In pursuit of the comprehensive profiling of the proteome, significant advances in technology have made the identification and quantitation of intact proteoforms from complex mixtures of proteins more routine, allowing analysis of the proteome from the 'Top-Down'. However, the number of proteoforms detected by Top-Down methodologies such as 2D-PAGE or mass spectrometry has not significantly increased since O'Farrell's paper when compared to Bottom-Up, peptide-centric techniques. This article explores and explains the numerous methodologies and technologies available to analyse the proteome from the Top-Down with a strong emphasis on the necessity to analyse intact proteoforms as a better indicator of changes in biology and phenotype. We arrive at the conclusion that the complete and comprehensive profiling of an organism's proteome is still, at present, beyond our reach but the continuing evolution of protein fractionation techniques and mass spectrometry brings comprehensive Top-Down proteome profiling closer.

Differential effect of TGFβ on the proteome of cancer associated fibroblasts and cancer epithelial cells in a co-culture approach - a short report.

PubMed

Koczorowska, Maria Magdalena; Friedemann, Charlotte; Geiger, Klaus; Follo, Marie; Biniossek, Martin Lothar; Schilling, Oliver

2017-12-01

Solid tumors contain various components that together form the tumor microenvironment. Cancer associated fibroblasts (CAFs) are capable of secreting and responding to signaling molecules and growth factors. Due to their role in tumor development, CAFs are considered as potential therapeutic targets. A prominent tumor-associated signaling molecule is transforming growth factor β (TGFβ), an inducer of epithelial-to-mesenchymal transition (EMT). The differential action of TGFβ on CAFs and ETCs (epithelial tumor cells) has recently gained interest. Here, we aimed to investigate the effects of TGFβ on CAFs and ETCs at the proteomic level. We established a 2D co-culture system of differentially fluorescently labeled CAFs and ETCs and stimulated this co-culture system with TGFβ. The respective cell types were separated using FACS and subjected to quantitative analyses of individual proteomes using mass spectrometry. We found that TGFβ treatment had a strong impact on the proteome composition of CAFs, whereas ETCs responded only marginally to TGFβ. Quantitative proteomic analyses of the different cell types revealed up-regulation of extracellular matrix (ECM) proteins in TGFβ treated CAFs. In addition, we found that the TGFβ treated CAFs exhibited increased N-cadherin levels. From our data we conclude that CAFs respond to TGFβ treatment by changing their proteome composition, while ETCs appear to be rather resilient.

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

PubMed Central

Carvalho, Paulo C; Lima, Diogo B; Leprevost, Felipe V; Santos, Marlon D M; Fischer, Juliana S G; Aquino, Priscila F; Moresco, James J; Yates, John R; Barbosa, Valmir C

2017-01-01

PatternLab for proteomics is an integrated computational environment that unifies several previously published modules for analyzing shotgun proteomic data. PatternLab contains modules for formatting sequence databases, performing peptide spectrum matching, statistically filtering and organizing shotgun proteomic data, extracting quantitative information from label-free and chemically labeled data, performing statistics for differential proteomics, displaying results in a variety of graphical formats, performing similarity-driven studies with de novo sequencing data, analyzing time-course experiments, and helping with the understanding of the biological significance of data in the light of the Gene Ontology. Here we describe PatternLab for proteomics 4.0, which closely knits together all of these modules in a self-contained environment, covering the principal aspects of proteomic data analysis as a freely available and easily installable software package. All updates to PatternLab, as well as all new features added to it, have been tested over the years on millions of mass spectra. PMID:26658470

USING GENOMICS AND PROTEOMICS TO DIAGNOSE EXPOSURE OF AQUATIC ORGANISMS TO ENVIRONMENTAL CONTAMINANTS

EPA Science Inventory

Advances in molecular biology allow the use of cutting-edge genomic and proteomic tools to assess the effects of environmental contaminants on aquatic organisms. Techniques are available to measure changes in expression of single genes (quantitative real-time PCR) or to measure g...

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

PubMed

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

2011-01-01

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

Improved Detection of HER2 by a Quasi-Targeted Proteomics Approach Using Aptamer-Peptide Probe and Liquid Chromatography-Tandem Mass Spectrometry.

PubMed

Zhou, Weixian; Xu, Feifei; Li, Danni; Chen, Yun

2018-03-01

Human epidermal growth factor receptor 2 (HER2)-positive breast cancer is a particularly aggressive type of the disease. To date, much evidence has indicated that accurate HER2 status detection is crucial for prognosis and treatment strategy selection. Thus, bioanalytical techniques for early and accurate detection of HER2 have the potential to improve patient care. Currently, the widely used immunohistochemical staining normally has problems with reproducibility and lack of standardization, resulting in poor concordance between laboratories. Aptamers are a good alternative, but the extent of their use in quantitative analysis of HER2 is limited because of the lack of effective detection methods. We developed a quasi-targeted proteomics assay and converted the HER2 signal into the mass response of reporter peptide by a combination of aptamer-peptide probe and LC-MS/MS. The selected aptamer-peptide probe consisted of aptamer HB5 and the substrate peptide GDKAVLGVDPFR that contained the reporter peptide AVLGVDPFR. After characterization of this newly synthesized probe (e.g., conjugation efficiency, stability, binding affinity, specificity, and digestion efficiency), probe binding and trypsin shaving conditions were optimized. The resulting limit of quantification for HER2 was 25 pmol/L. Then, the quasi-targeted proteomics assay was applied to determine the HER2 concentrations in the HER2-positive breast cancer cells BT474 and SK-BR-3, the HER2-negative breast cancer cells MDA-MB-231 and MCF-7, and 36 pairs of human breast primary tumors and adjacent normal tissue samples. The results were highly concordant with those obtained by immunohistochemistry with reflex testing by fluorescent in situ hybridization. Quasi-targeted proteomics can be a quantitative alternative for HER2 detection. © 2017 American Association for Clinical Chemistry.

Quantitative Proteomics Analysis of Herbaceous Peony in Response to Paclobutrazol Inhibition of Lateral Branching

PubMed Central

Zhao, Daqiu; Gong, Saijie; Hao, Zhaojun; Meng, Jiasong; Tao, Jun

2015-01-01

Herbaceous peony (Paeonia lactiflora Pall.) is an emerging high-grade cut flower worldwide, which is usually used in wedding bouquets and known as the “wedding flower”. However, abundant lateral branches appear frequently in some excellent cultivars, and a lack of a method to remove Paeonia lactiflora lateral branches other than inefficient artificial methods is an obstacle for improving the quality of its cut flowers. In this study, paclobutrazol (PBZ) application was found to inhibit the growth of lateral branches in Paeonia lactiflora for the first time, including 96.82% decreased lateral bud number per branch, 77.79% and 42.31% decreased length and diameter of lateral branches, respectively, declined cell wall materials and changed microstructures. Subsequently, isobaric tag for relative and absolute quantitation (iTRAQ) technology was used for quantitative proteomics analysis of lateral branches under PBZ application and control. The results indicated that 178 differentially expressed proteins (DEPs) successfully obtained, 98 DEPs were up-regulated and 80 DEPs were down-regulated. Thereafter, 34 candidate DEPs associated with the inhibited growth of lateral branches were screened according to their function and classification. These PBZ-stress responsive candidate DEPs were involved in eight biological processes, which played a very important role in the growth and development of lateral branches together with the response to PBZ stress. These results provide a better understanding of the molecular theoretical basis for removing Paeonia lactiflora lateral branches using PBZ application. PMID:26473855

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

PubMed Central

Gu, Liqing; Robinson, Renã A. S.

2016-01-01

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

A comprehensive evaluation of popular proteomics software workflows for label-free proteome quantification and imputation.

PubMed

Välikangas, Tommi; Suomi, Tomi; Elo, Laura L

2017-05-31

Label-free mass spectrometry (MS) has developed into an important tool applied in various fields of biological and life sciences. Several software exist to process the raw MS data into quantified protein abundances, including open source and commercial solutions. Each software includes a set of unique algorithms for different tasks of the MS data processing workflow. While many of these algorithms have been compared separately, a thorough and systematic evaluation of their overall performance is missing. Moreover, systematic information is lacking about the amount of missing values produced by the different proteomics software and the capabilities of different data imputation methods to account for them.In this study, we evaluated the performance of five popular quantitative label-free proteomics software workflows using four different spike-in data sets. Our extensive testing included the number of proteins quantified and the number of missing values produced by each workflow, the accuracy of detecting differential expression and logarithmic fold change and the effect of different imputation and filtering methods on the differential expression results. We found that the Progenesis software performed consistently well in the differential expression analysis and produced few missing values. The missing values produced by the other software decreased their performance, but this difference could be mitigated using proper data filtering or imputation methods. Among the imputation methods, we found that the local least squares (lls) regression imputation consistently increased the performance of the software in the differential expression analysis, and a combination of both data filtering and local least squares imputation increased performance the most in the tested data sets. © The Author 2017. Published by Oxford University Press.

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

PubMed

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

2016-08-16

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

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

PubMed Central

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

2016-01-01

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

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

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

PubMed

Byrum, Stephanie D; Larson, Signe K; Avaritt, Nathan L; Moreland, Linley E; Mackintosh, Samuel G; Cheung, Wang L; Tackett, Alan J

2013-03-01

Molecular pathways regulating melanoma initiation and progression are potential targets of therapeutic development for this aggressive cancer. Identification and molecular analysis of these pathways in patients has been primarily restricted to targeted studies on individual proteins. Here, we report the most comprehensive analysis of formalin-fixed paraffin-embedded human melanoma tissues using quantitative proteomics. From 61 patient samples, we identified 171 proteins varying in abundance among benign nevi, primary melanoma, and metastatic melanoma. Seventy-three percent of these proteins were validated by immunohistochemistry staining of malignant melanoma tissues from the Human Protein Atlas database. Our results reveal that molecular pathways involved with tumor cell proliferation, motility, and apoptosis are mis-regulated in melanoma. These data provide the most comprehensive proteome resource on patient melanoma and reveal insight into the molecular mechanisms driving melanoma progression.

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.

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

PubMed Central

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

2017-01-01

Quantitative proteomics strategies – which are playing important roles in the expanding field of plant molecular systems biology – are traditionally designated as either hypothesis driven or non-hypothesis driven. Many of these strategies aim to select individual peptide ions for tandem mass spectrometry (MS/MS), and to do this mixed hypothesis driven and non-hypothesis driven approaches are theoretically simple to implement. In-depth investigations into the efficacies of such approaches have, however, yet to be described. In this study, using combined samples of unlabeled and metabolically 15N-labeled Arabidopsis thaliana proteins, we investigate the mixed use of targeted data acquisition (TDA) and data dependent acquisition (DDA) – referred to as TDA/DDA – to facilitate both hypothesis driven and non-hypothesis driven quantitative data collection in individual LC-MS/MS experiments. To investigate TDA/DDA for hypothesis driven data collection, 7 miRNA target proteins of differing size and abundance were targeted using inclusion lists comprised of 1558 m/z values, using 3 different TDA/DDA experimental designs. In samples in which targeted peptide ions were of particularly low abundance (i.e., predominantly only marginally above mass analyser detection limits), TDA/DDA produced statistically significant increases in the number of targeted peptides identified (230 ± 8 versus 80 ± 3 for DDA; p = 1.1 × 10-3) and quantified (35 ± 3 versus 21 ± 2 for DDA; p = 0.038) per experiment relative to the use of DDA only. These expected improvements in hypothesis driven data collection were observed alongside unexpected improvements in non-hypothesis driven data collection. Untargeted peptide ions with m/z values matching those in inclusion lists were repeatedly identified and quantified across technical replicate TDA/DDA experiments, resulting in significant increases in the percentages of proteins repeatedly quantified in TDA/DDA experiments only relative to DDA experiments only (33.0 ± 2.6% versus 8.0 ± 2.7%, respectively; p = 0.011). These results were observed together with uncompromised broad-scale MS/MS data collection in TDA/DDA experiments relative to DDA experiments. Using our observations we provide guidelines for TDA/DDA method design for quantitative plant proteomics studies, and suggest that TDA/DDA is a broadly underutilized proteomics data acquisition strategy. PMID:29021799

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

PubMed

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

2015-06-06

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

A Crowdsourcing Approach to Developing and Assessing Prediction Algorithms for AML Prognosis

PubMed Central

Noren, David P.; Long, Byron L.; Norel, Raquel; Rrhissorrakrai, Kahn; Hess, Kenneth; Hu, Chenyue Wendy; Bisberg, Alex J.; Schultz, Andre; Engquist, Erik; Liu, Li; Lin, Xihui; Chen, Gregory M.; Xie, Honglei; Hunter, Geoffrey A. M.; Norman, Thea; Friend, Stephen H.; Stolovitzky, Gustavo; Kornblau, Steven; Qutub, Amina A.

2016-01-01

Acute Myeloid Leukemia (AML) is a fatal hematological cancer. The genetic abnormalities underlying AML are extremely heterogeneous among patients, making prognosis and treatment selection very difficult. While clinical proteomics data has the potential to improve prognosis accuracy, thus far, the quantitative means to do so have yet to be developed. Here we report the results and insights gained from the DREAM 9 Acute Myeloid Prediction Outcome Prediction Challenge (AML-OPC), a crowdsourcing effort designed to promote the development of quantitative methods for AML prognosis prediction. We identify the most accurate and robust models in predicting patient response to therapy, remission duration, and overall survival. We further investigate patient response to therapy, a clinically actionable prediction, and find that patients that are classified as resistant to therapy are harder to predict than responsive patients across the 31 models submitted to the challenge. The top two performing models, which held a high sensitivity to these patients, substantially utilized the proteomics data to make predictions. Using these models, we also identify which signaling proteins were useful in predicting patient therapeutic response. PMID:27351836

Trends in mass spectrometry instrumentation for proteomics

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

Smith, Richard D.

2002-12-01

Mass spectrometry has become a primary tool for proteomics due to its capabilities for rapid and sensitive protein identification and quantitation. It is now possible to identify thousands of proteins from microgram sample quantities in a single day and to quantify relative protein abundances. However, the needs for increased capabilities for proteome measurements are immense and are now driving both new strategies and instrument advances. These developments include those based on integration with multi-dimensional liquid separations and high accuracy mass measurements, and promise more than order of magnitude improvements in sensitivity, dynamic range, and throughput for proteomic analyses in themore » near future.« less

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

Comparison of DIGE and post-stained gel electrophoresis with both traditional and SameSpots analysis for quantitative proteomics.

PubMed

Karp, Natasha A; Feret, Renata; Rubtsov, Denis V; Lilley, Kathryn S

2008-03-01

2-DE is an important tool in quantitative proteomics. Here, we compare the deep purple (DP) system with DIGE using both a traditional and the SameSpots approach to gel analysis. Missing values in the traditional approach were found to be a significant issue for both systems. SameSpots attempts to address the missing value problem. SameSpots was found to increase the proportion of low volume data for DP but not for DIGE. For all the analysis methods applied in this study, the assumptions of parametric tests were met. Analysis of the same images gave significantly lower noise with SameSpots (over traditional) for DP, but no difference for DIGE. We propose that SameSpots gave lower noise with DP due to the stabilisation of the spot area by the common spot outline, but this was not seen with DIGE due to the co-detection process which stabilises the area selected. For studies where measurement of small abundance changes is required, a cost-benefit analysis highlights that DIGE was significantly cheaper regardless of the analysis methods. For studies analysing large changes, DP with SameSpots could be an effective alternative to DIGE but this will be dependent on the biological noise of the system under investigation.

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

PubMed Central

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

2016-01-01

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

The jmzQuantML programming interface and validator for the mzQuantML data standard.

PubMed

Qi, Da; Krishna, Ritesh; Jones, Andrew R

2014-03-01

The mzQuantML standard from the HUPO Proteomics Standards Initiative has recently been released, capturing quantitative data about peptides and proteins, following analysis of MS data. We present a Java application programming interface (API) for mzQuantML called jmzQuantML. The API provides robust bridges between Java classes and elements in mzQuantML files and allows random access to any part of the file. The API provides read and write capabilities, and is designed to be embedded in other software packages, enabling mzQuantML support to be added to proteomics software tools (http://code.google.com/p/jmzquantml/). The mzQuantML standard is designed around a multilevel validation system to ensure that files are structurally and semantically correct for different proteomics quantitative techniques. In this article, we also describe a Java software tool (http://code.google.com/p/mzquantml-validator/) for validating mzQuantML files, which is a formal part of the data standard. © 2014 The Authors. Proteomics published by Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

Proteomic Analysis of Pathogenic Fungi Reveals Highly Expressed Conserved Cell Wall Proteins

PubMed Central

Champer, Jackson; Ito, James I.; Clemons, Karl V.; Stevens, David A.; Kalkum, Markus

2016-01-01

We are presenting a quantitative proteomics tally of the most commonly expressed conserved fungal proteins of the cytosol, the cell wall, and the secretome. It was our goal to identify fungi-typical proteins that do not share significant homology with human proteins. Such fungal proteins are of interest to the development of vaccines or drug targets. Protein samples were derived from 13 fungal species, cultured in rich or in minimal media; these included clinical isolates of Aspergillus, Candida, Mucor, Cryptococcus, and Coccidioides species. Proteomes were analyzed by quantitative MSE (Mass Spectrometry—Elevated Collision Energy). Several thousand proteins were identified and quantified in total across all fractions and culture conditions. The 42 most abundant proteins identified in fungal cell walls or supernatants shared no to very little homology with human proteins. In contrast, all but five of the 50 most abundant cytosolic proteins had human homologs with sequence identity averaging 59%. Proteomic comparisons of the secreted or surface localized fungal proteins highlighted conserved homologs of the Aspergillus fumigatus proteins 1,3-β-glucanosyltransferases (Bgt1, Gel1-4), Crf1, Ecm33, EglC, and others. The fact that Crf1 and Gel1 were previously shown to be promising vaccine candidates, underlines the value of the proteomics data presented here. PMID:26878023

The Response of the Root Proteome to the Synthetic Strigolactone GR24 in Arabidopsis*

PubMed Central

Walton, Alan; Stes, Elisabeth; Goeminne, Geert; Braem, Lukas; Vuylsteke, Marnik; Matthys, Cedrick; De Cuyper, Carolien; Staes, An; Vandenbussche, Jonathan; Boyer, François-Didier; Vanholme, Ruben; Fromentin, Justine; Boerjan, Wout; Gevaert, Kris; Goormachtig, Sofie

2016-01-01

Strigolactones are plant metabolites that act as phytohormones and rhizosphere signals. Whereas most research on unraveling the action mechanisms of strigolactones is focused on plant shoots, we investigated proteome adaptation during strigolactone signaling in the roots of Arabidopsis thaliana. Through large-scale, time-resolved, and quantitative proteomics, the impact of the strigolactone analog rac-GR24 was elucidated on the root proteome of the wild type and the signaling mutant more axillary growth 2 (max2). Our study revealed a clear MAX2-dependent rac-GR24 response: an increase in abundance of enzymes involved in flavonol biosynthesis, which was reduced in the max2–1 mutant. Mass spectrometry-driven metabolite profiling and thin-layer chromatography experiments demonstrated that these changes in protein expression lead to the accumulation of specific flavonols. Moreover, quantitative RT-PCR revealed that the flavonol-related protein expression profile was caused by rac-GR24-induced changes in transcript levels of the corresponding genes. This induction of flavonol production was shown to be activated by the two pure enantiomers that together make up rac-GR24. Finally, our data provide much needed clues concerning the multiple roles played by MAX2 in the roots and a comprehensive view of the rac-GR24-induced response in the root proteome. PMID:27317401

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

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

PubMed

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

2017-09-01

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

An automated method for detecting alternatively spliced protein domains.

PubMed

Coelho, Vitor; Sammeth, Michael

2018-06-01

Alternative splicing (AS) has been demonstrated to play a role in shaping eukaryotic gene diversity at the transcriptional level. However, the impact of AS on the proteome is still controversial. Studies that seek to explore the effect of AS at the proteomic level are hampered by technical difficulties in the cumbersome process of casting forth and back between genome, transcriptome and proteome space coordinates, and the naïve prediction of protein domains in the presence of AS suffers many redundant sequence scans that emerge from constitutively spliced regions that are shared between alternative products of a gene. We developed the AstaFunk pipeline that computes for every generic transcriptome all domains that are altered by AS events in a systematic and efficient manner. In a nutshell, our method employs Viterbi dynamic programming, which guarantees to find all score-optimal hits of the domains under consideration, while complementary optimisations at different levels avoid redundant and other irrelevant computations. We evaluate AstaFunk qualitatively and quantitatively using RNAseq in well-studied genes with AS, and on large-scale employing entire transcriptomes. Our study confirms complementary reports that the effect of most AS events on the proteome seems to be rather limited, but our results also pinpoint several cases where AS could have a major impact on the function of a protein domain. The JAVA implementation of AstaFunk is available as an open source project on http://astafunk.sammeth.net. micha@sammeth.net. Supplementary data are available at Bioinformatics online.

Skyline: an open source document editor for creating and analyzing targeted proteomics experiments

PubMed Central

MacLean, Brendan; Tomazela, Daniela M.; Shulman, Nicholas; Chambers, Matthew; Finney, Gregory L.; Frewen, Barbara; Kern, Randall; Tabb, David L.; Liebler, Daniel C.; MacCoss, Michael J.

2010-01-01

Summary: Skyline is a Windows client application for targeted proteomics method creation and quantitative data analysis. It is open source and freely available for academic and commercial use. The Skyline user interface simplifies the development of mass spectrometer methods and the analysis of data from targeted proteomics experiments performed using selected reaction monitoring (SRM). Skyline supports using and creating MS/MS spectral libraries from a wide variety of sources to choose SRM filters and verify results based on previously observed ion trap data. Skyline exports transition lists to and imports the native output files from Agilent, Applied Biosystems, Thermo Fisher Scientific and Waters triple quadrupole instruments, seamlessly connecting mass spectrometer output back to the experimental design document. The fast and compact Skyline file format is easily shared, even for experiments requiring many sample injections. A rich array of graphs displays results and provides powerful tools for inspecting data integrity as data are acquired, helping instrument operators to identify problems early. The Skyline dynamic report designer exports tabular data from the Skyline document model for in-depth analysis with common statistical tools. Availability: Single-click, self-updating web installation is available at http://proteome.gs.washington.edu/software/skyline. This web site also provides access to instructional videos, a support board, an issues list and a link to the source code project. Contact: brendanx@u.washington.edu Supplementary information: Supplementary data are available at Bioinformatics online. PMID:20147306

Method optimization for proteomic analysis of soybean leaf: Improvements in identification of new and low-abundance proteins

PubMed Central

Mesquita, Rosilene Oliveira; de Almeida Soares, Eduardo; de Barros, Everaldo Gonçalves; Loureiro, Marcelo Ehlers

2012-01-01

The most critical step in any proteomic study is protein extraction and sample preparation. Better solubilization increases the separation and resolution of gels, allowing identification of a higher number of proteins and more accurate quantitation of differences in gene expression. Despite the existence of published results for the optimization of proteomic analyses of soybean seeds, no comparable data are available for proteomic studies of soybean leaf tissue. In this work we have tested the effects of modification of a TCA-acetone method on the resolution of 2-DE gels of leaves and roots of soybean. Better focusing was obtained when both mercaptoethanol and dithiothreitol were used in the extraction buffer simultaneously. Increasing the number of washes of TCA precipitated protein with acetone, using a final wash with 80% ethanol and using sonication to ressuspend the pellet increased the number of detected proteins as well the resolution of the 2-DE gels. Using this approach we have constructed a soybean protein map. The major group of identified proteins corresponded to genes of unknown function. The second and third most abundant groups of proteins were composed of photosynthesis and metabolism related genes. The resulting protocol improved protein solubility and gel resolution allowing the identification of 122 soybean leaf proteins, 72 of which were not detected in other published soybean leaf 2-DE gel datasets, including a transcription factor and several signaling proteins. PMID:22802721

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

NASA Astrophysics Data System (ADS)

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

2016-03-01

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

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

PubMed Central

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

2014-01-01

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

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

PubMed

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

2016-03-09

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

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

PubMed Central

2017-01-01

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

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

PubMed

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

2017-04-01

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

Targeted proteomics identifies liquid-biopsy signatures for extracapsular prostate cancer

PubMed Central

Kim, Yunee; Jeon, Jouhyun; Mejia, Salvador; Yao, Cindy Q; Ignatchenko, Vladimir; Nyalwidhe, Julius O; Gramolini, Anthony O; Lance, Raymond S; Troyer, Dean A; Drake, Richard R; Boutros, Paul C; Semmes, O. John; Kislinger, Thomas

2016-01-01

Biomarkers are rapidly gaining importance in personalized medicine. Although numerous molecular signatures have been developed over the past decade, there is a lack of overlap and many biomarkers fail to validate in independent patient cohorts and hence are not useful for clinical application. For these reasons, identification of novel and robust biomarkers remains a formidable challenge. We combine targeted proteomics with computational biology to discover robust proteomic signatures for prostate cancer. Quantitative proteomics conducted in expressed prostatic secretions from men with extraprostatic and organ-confined prostate cancers identified 133 differentially expressed proteins. Using synthetic peptides, we evaluate them by targeted proteomics in a 74-patient cohort of expressed prostatic secretions in urine. We quantify a panel of 34 candidates in an independent 207-patient cohort. We apply machine-learning approaches to develop clinical predictive models for prostate cancer diagnosis and prognosis. Our results demonstrate that computationally guided proteomics can discover highly accurate non-invasive biomarkers. PMID:27350604

Quantitative Assays for RAS Pathway Proteins and Phosphorylation States

Cancer.gov

The NCI CPTAC program is applying its expertise in quantitative proteomics to develop assays for RAS pathway proteins. Targets include key phosphopeptides that should increase our understanding of how the RAS pathway is regulated.

Quantitative measurement of intact alpha-synuclein proteoforms from post-mortem control and Parkinson's disease brain tissue by intact protein mass spectrometry.

PubMed

Kellie, John F; Higgs, Richard E; Ryder, John W; Major, Anthony; Beach, Thomas G; Adler, Charles H; Merchant, Kalpana; Knierman, Michael D

2014-07-23

A robust top down proteomics method is presented for profiling alpha-synuclein species from autopsied human frontal cortex brain tissue from Parkinson's cases and controls. The method was used to test the hypothesis that pathology associated brain tissue will have a different profile of post-translationally modified alpha-synuclein than the control samples. Validation of the sample processing steps, mass spectrometry based measurements, and data processing steps were performed. The intact protein quantitation method features extraction and integration of m/z data from each charge state of a detected alpha-synuclein species and fitting of the data to a simple linear model which accounts for concentration and charge state variability. The quantitation method was validated with serial dilutions of intact protein standards. Using the method on the human brain samples, several previously unreported modifications in alpha-synuclein were identified. Low levels of phosphorylated alpha synuclein were detected in brain tissue fractions enriched for Lewy body pathology and were marginally significant between PD cases and controls (p = 0.03).

Precise quantitation of 136 urinary proteins by LC/MRM-MS using stable isotope labeled peptides as internal standards for biomarker discovery and/or verification studies.

PubMed

Percy, Andrew J; Yang, Juncong; Hardie, Darryl B; Chambers, Andrew G; Tamura-Wells, Jessica; Borchers, Christoph H

2015-06-15

Spurred on by the growing demand for panels of validated disease biomarkers, increasing efforts have focused on advancing qualitative and quantitative tools for more highly multiplexed and sensitive analyses of a multitude of analytes in various human biofluids. In quantitative proteomics, evolving strategies involve the use of the targeted multiple reaction monitoring (MRM) mode of mass spectrometry (MS) with stable isotope-labeled standards (SIS) used for internal normalization. Using that preferred approach with non-invasive urine samples, we have systematically advanced and rigorously assessed the methodology toward the precise quantitation of the largest, multiplexed panel of candidate protein biomarkers in human urine to date. The concentrations of the 136 proteins span >5 orders of magnitude (from 8.6 μg/mL to 25 pg/mL), with average CVs of 8.6% over process triplicate. Detailed here is our quantitative method, the analysis strategy, a feasibility application to prostate cancer samples, and a discussion of the utility of this method in translational studies. Copyright © 2015 Elsevier Inc. All rights reserved.

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

PubMed Central

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

2014-01-01

Recent advances in quantitative proteomic technology have enabled the large-scale validation of biomarkers. We here performed a quantitative proteomic analysis of membrane fractions from colorectal cancer tissue to discover biomarker candidates, and then extensively validated the candidate proteins identified. A total of 5566 proteins were identified in six tissue samples, each of which was obtained from polyps and cancer with and without metastasis. GO cellular component analysis predicted that 3087 of these proteins were membrane proteins, whereas TMHMM algorithm predicted that 1567 proteins had a transmembrane domain. Differences were observed in the expression of 159 membrane proteins and 55 extracellular proteins between polyps and cancer without metastasis, while the expression of 32 membrane proteins and 17 extracellular proteins differed between cancer with and without metastasis. A total of 105 of these biomarker candidates were quantitated using selected (or multiple) reaction monitoring (SRM/MRM) with stable synthetic isotope-labeled peptides as an internal control. The results obtained revealed differences in the expression of 69 of these proteins, and this was subsequently verified in an independent set of patient samples (polyps (n = 10), cancer without metastasis (n = 10), cancer with metastasis (n = 10)). Significant differences were observed in the expression of 44 of these proteins, including ITGA5, GPRC5A, PDGFRB, and TFRC, which have already been shown to be overexpressed in colorectal cancer, as well as proteins with unknown function, such as C8orf55. The expression of C8orf55 was also shown to be high not only in colorectal cancer, but also in several cancer tissues using a multicancer tissue microarray, which included 1150 cores from 14 cancer tissues. This is the largest verification study of biomarker candidate membrane proteins to date; our methods for biomarker discovery and subsequent validation using SRM/MRM will contribute to the identification of useful biomarker candidates for various cancers. Data are available via ProteomeXchange with identifier PXD000851. PMID:24687888

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

PubMed

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

2014-06-01

Recent advances in quantitative proteomic technology have enabled the large-scale validation of biomarkers. We here performed a quantitative proteomic analysis of membrane fractions from colorectal cancer tissue to discover biomarker candidates, and then extensively validated the candidate proteins identified. A total of 5566 proteins were identified in six tissue samples, each of which was obtained from polyps and cancer with and without metastasis. GO cellular component analysis predicted that 3087 of these proteins were membrane proteins, whereas TMHMM algorithm predicted that 1567 proteins had a transmembrane domain. Differences were observed in the expression of 159 membrane proteins and 55 extracellular proteins between polyps and cancer without metastasis, while the expression of 32 membrane proteins and 17 extracellular proteins differed between cancer with and without metastasis. A total of 105 of these biomarker candidates were quantitated using selected (or multiple) reaction monitoring (SRM/MRM) with stable synthetic isotope-labeled peptides as an internal control. The results obtained revealed differences in the expression of 69 of these proteins, and this was subsequently verified in an independent set of patient samples (polyps (n = 10), cancer without metastasis (n = 10), cancer with metastasis (n = 10)). Significant differences were observed in the expression of 44 of these proteins, including ITGA5, GPRC5A, PDGFRB, and TFRC, which have already been shown to be overexpressed in colorectal cancer, as well as proteins with unknown function, such as C8orf55. The expression of C8orf55 was also shown to be high not only in colorectal cancer, but also in several cancer tissues using a multicancer tissue microarray, which included 1150 cores from 14 cancer tissues. This is the largest verification study of biomarker candidate membrane proteins to date; our methods for biomarker discovery and subsequent validation using SRM/MRM will contribute to the identification of useful biomarker candidates for various cancers. Data are available via ProteomeXchange with identifier PXD000851. © 2014 by The American Society for Biochemistry and Molecular Biology, Inc.

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

Common and Specific Protein Accumulation Patterns in Different Albino/Pale-Green Mutants Reveals Regulon Organization at the Proteome Level1[W

PubMed Central

Motohashi, Reiko; Rödiger, Anja; Agne, Birgit; Baerenfaller, Katja; Baginsky, Sacha

2012-01-01

Research interest in proteomics is increasingly shifting toward the reverse genetic characterization of gene function at the proteome level. In plants, several distinct gene defects perturb photosynthetic capacity, resulting in the loss of chlorophyll and an albino or pale-green phenotype. Because photosynthesis is interconnected with the entire plant metabolism and its regulation, all albino plants share common characteristics that are determined by the switch from autotrophic to heterotrophic growth. Reverse genetic characterizations of such plants often cannot distinguish between specific consequences of a gene defect from generic effects in response to perturbations in photosynthetic capacity. Here, we set out to define common and specific features of protein accumulation in three different albino/pale-green plant lines. Using quantitative proteomics, we report a common molecular phenotype that connects the loss of photosynthetic capacity with other chloroplast and cellular functions, such as protein folding and stability, plastid protein import, and the expression of stress-related genes. Surprisingly, we do not find significant differences in the expression of key transcriptional regulators, suggesting that substantial regulation occurs at the posttranscriptional level. We examine the influence of different normalization schemes on the quantitative proteomics data and report all identified proteins along with their fold changes and P values in albino plants in comparison with the wild type. Our analysis provides initial guidance for the distinction between general and specific adaptations of the proteome in photosynthesis-impaired plants. PMID:23027667

Evaluation of Three Protein-Extraction Methods for Proteome Analysis of Maize Leaf Midrib, a Compound Tissue Rich in Sclerenchyma Cells.

PubMed

Wang, Ning; Wu, Xiaolin; Ku, Lixia; Chen, Yanhui; Wang, Wei

2016-01-01

Leaf morphology is closely related to the growth and development of maize (Zea mays L.) plants and final kernel production. As an important part of the maize leaf, the midrib holds leaf blades in the aerial position for maximum sunlight capture. Leaf midribs of adult plants contain substantial sclerenchyma cells with heavily thickened and lignified secondary walls and have a high amount of phenolics, making protein extraction and proteome analysis difficult in leaf midrib tissue. In the present study, three protein-extraction methods that are commonly used in plant proteomics, i.e., phenol extraction, TCA/acetone extraction, and TCA/acetone/phenol extraction, were qualitatively and quantitatively evaluated based on 2DE maps and MS/MS analysis using the midribs of the 10th newly expanded leaves of maize plants. Microscopy revealed the existence of substantial amounts of sclerenchyma underneath maize midrib epidermises (particularly abaxial epidermises). The spot-number order obtained via 2DE mapping was as follows: phenol extraction (655) > TCA/acetone extraction (589) > TCA/acetone/phenol extraction (545). MS/MS analysis identified a total of 17 spots that exhibited 2-fold changes in abundance among the three methods (using phenol extraction as a control). Sixteen of the proteins identified were hydrophilic, with GRAVY values ranging from -0.026 to -0.487. For all three methods, we were able to obtain high-quality protein samples and good 2DE maps for the maize leaf midrib. However, phenol extraction produced a better 2DE map with greater resolution between spots, and TCA/acetone extraction produced higher protein yields. Thus, this paper includes a discussion regarding the possible reasons for differential protein extraction among the three methods. This study provides useful information that can be used to select suitable protein extraction methods for the proteome analysis of recalcitrant plant tissues that are rich in sclerenchyma cells.

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

Quantifying Ubiquitin Signaling

PubMed Central

Ordureau, Alban; Münch, Christian; Harper, J. Wade

2015-01-01

Ubiquitin (UB)-driven signaling systems permeate biology, and are often integrated with other types of post-translational modifications (PTMs), most notably phosphorylation. Flux through such pathways is typically dictated by the fractional stoichiometry of distinct regulatory modifications and protein assemblies as well as the spatial organization of pathway components. Yet, we rarely understand the dynamics and stoichiometry of rate-limiting intermediates along a reaction trajectory. Here, we review how quantitative proteomic tools and enrichment strategies are being used to quantify UB-dependent signaling systems, and to integrate UB signaling with regulatory phosphorylation events. A key regulatory feature of ubiquitylation is that the identity of UB chain linkage types can control downstream processes. We also describe how proteomic and enzymological tools can be used to identify and quantify UB chain synthesis and linkage preferences. The emergence of sophisticated quantitative proteomic approaches will set a new standard for elucidating biochemical mechanisms of UB-driven signaling systems. PMID:26000850

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

PubMed

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

2016-06-15

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

MRM as a discovery tool?

PubMed

Rudnick, Paul A

2015-04-01

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

Deciphering Multifactorial Resistance Phenotypes in Acinetobacter baumannii by Genomics and Targeted Label-free Proteomics.

PubMed

Cecchini, Tiphaine; Yoon, Eun-Jeong; Charretier, Yannick; Bardet, Chloé; Beaulieu, Corinne; Lacoux, Xavier; Docquier, Jean-Denis; Lemoine, Jerome; Courvalin, Patrice; Grillot-Courvalin, Catherine; Charrier, Jean-Philippe

2018-03-01

Resistance to β-lactams in Acinetobacter baumannii involves various mechanisms. To decipher them, whole genome sequencing (WGS) and real-time quantitative polymerase chain reaction (RT-qPCR) were complemented by mass spectrometry (MS) in selected reaction monitoring mode (SRM) in 39 clinical isolates. The targeted label-free proteomic approach enabled, in one hour and using a single method, the quantitative detection of 16 proteins associated with antibiotic resistance: eight acquired β-lactamases ( i.e. GES, NDM-1, OXA-23, OXA-24, OXA-58, PER, TEM-1, and VEB), two resident β-lactamases ( i.e. ADC and OXA-51-like) and six components of the two major efflux systems ( i.e. AdeABC and AdeIJK). Results were normalized using "bacterial quantotypic peptides," i.e. peptide markers of the bacterial quantity, to obtain precise protein quantitation (on average 8.93% coefficient of variation for three biological replicates). This allowed to correlate the levels of resistance to β-lactam with those of the production of acquired as well as resident β-lactamases or of efflux systems. SRM detected enhanced ADC or OXA-51-like production and absence or increased efflux pump production. Precise protein quantitation was particularly valuable to detect resistance mechanisms mediated by regulated genes or by overexpression of chromosomal genes. Combination of WGS and MS, two orthogonal and complementary techniques, allows thereby interpretation of the resistance phenotypes at the molecular level. © 2018 by The American Society for Biochemistry and Molecular Biology, Inc.

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

A study protocol for quantitative targeted absolute proteomics (QTAP) by LC-MS/MS: application for inter-strain differences in protein expression levels of transporters, receptors, claudin-5, and marker proteins at the blood–brain barrier in ddY, FVB, and C57BL/6J mice

PubMed Central

2013-01-01

Proteomics has opened a new horizon in biological sciences. Global proteomic analysis is a promising technology for the discovery of thousands of proteins, post-translational modifications, polymorphisms, and molecular interactions in a variety of biological systems. The activities and roles of the identified proteins must also be elucidated, but this is complicated by the inability of conventional proteomic methods to yield quantitative information for protein expression. Thus, a variety of biological systems remain “black boxes”. Quantitative targeted absolute proteomics (QTAP) enables the determination of absolute expression levels (mol) of any target protein, including low-abundance functional proteins, such as transporters and receptors. Therefore, QTAP will be useful for understanding the activities and roles of individual proteins and their differences, including normal/disease, human/animal, or in vitro/in vivo. Here, we describe the study protocols and precautions for QTAP experiments including in silico target peptide selection, determination of peptide concentration by amino acid analysis, setup of selected/multiple reaction monitoring (SRM/MRM) analysis in liquid chromatography–tandem mass spectrometry, preparation of protein samples (brain capillaries and plasma membrane fractions) followed by the preparation of peptide samples, simultaneous absolute quantification of target proteins by SRM/MRM analysis, data analysis, and troubleshooting. An application of QTAP in biological sciences was introduced that utilizes data from inter-strain differences in the protein expression levels of transporters, receptors, tight junction proteins and marker proteins at the blood–brain barrier in ddY, FVB, and C57BL/6J mice. Among 18 molecules, 13 (abcb1a/mdr1a/P-gp, abcc4/mrp4, abcg2/bcrp, slc2a1/glut1, slc7a5/lat1, slc16a1/mct1, slc22a8/oat3, insr, lrp1, tfr1, claudin-5, Na+/K+-ATPase, and γ-gtp) were detected in the isolated brain capillaries, and their protein expression levels were within a range of 0.637-101 fmol/μg protein. The largest difference in the levels between the three strains was 2.2-fold for 13 molecules, although bcrp and mct1 displayed statistically significant differences between C57BL/6J and the other strain(s). Highly sensitive simultaneous absolute quantification achieved by QTAP will increase the usefulness of proteomics in biological sciences and is expected to advance the new research field of pharmacoproteomics (PPx). PMID:23758935

Genome-wide proteomics analysis on longissimus muscles in Qinchuan beef cattle.

PubMed

He, Hua; Chen, Si; Liang, Wei; Liu, Xiaolin

2017-04-01

To gain further insight into the molecular mechanism of bovine muscle development, we combined mass spectrometry characterization of proteins with Illumina deep sequencing of RNAs obtained from bovine longissimus muscle (LD) at prenatal and postnatal stages. For the proteomic study, each group of LD proteins was extracted and labeled using isobaric tags for relative and absolute quantitation (iTRAQ) method. Among the 1321 proteins identified from six samples, 390 proteins were differentially expressed in embryos at day 135 post-fertilization (Emb135d) vs. 30-month-old adult cattle (Emb135d vs. 30M) samples. Gene Ontology, Cluster of Orthologous Groups and Kyoto Encyclopedia of Genes and Genomes analyses were further conducted to better understand the different functions. Furthermore, we analyzed the relationship between transcript and protein regulation between samples by direct comparison of expression levels from transcriptomic and iTRAQ-based proteomics. Association results indicated that 1295 of 1321 proteins could be mapped to transcriptome sequencing data. This study provides the most comprehensive, targeted survey of bovine LD proteins to date and has shown the power of combining transcriptomic and proteomic approaches to provide molecular insights for understanding the developmental characteristics in bovine muscle, and even in other mammals. © 2016 Stichting International Foundation for Animal Genetics.

Proteomic analysis of urine in rats chronically exposed to fluoride.

PubMed

Kobayashi, Claudia Ayumi Nakai; Leite, Aline de Lima; da Silva, Thelma Lopes; dos Santos, Lucilene Delazari; Nogueira, Fábio César Sousa; Santos, Keity Souza; de Oliveira, Rodrigo Cardoso; Palma, Mario Sérgio; Domont, Gilberto Barbosa; Buzalaf, Marília Afonso Rabelo

2011-01-01

Urine is an ideal source of materials to search for potential disease-related biomarkers as it is produced by the affected tissues and can be easily obtained by noninvasive methods. 2-DE-based proteomic approach was used to better understand the molecular mechanisms of injury induced by fluoride (F(-)) and define potential biomarkers of dental fluorosis. Three groups of weanling male Wistar rats were treated with drinking water containing 0 (control), 5, or 50 ppm F(-) for 60 days (n = 15/group). During the experimental period, the animals were kept individually in metabolic cages, to analyze the water and food consumption, as well as fecal and urinary F(-) excretion. Urinary proteome profiles were examined using 2-DE and Colloidal Coomassie Brilliant Blue staining. A dose-response regarding F(-) intake and excretion was detected. Quantitative intensity analysis revealed 8, 11, and 8 significantly altered proteins between control vs. 5 ppm F(-), control vs. 50 ppm F(-) and 5 ppm F(-) vs. 50 ppm F(-) groups, respectively. Two proteins regulated by androgens (androgen-regulated 20-KDa protein and α-2μ-globulin) and one related to detoxification (aflatoxin-B1-aldehyde-reductase) were identified by MALDI-TOF-TOF MS/MS. Thus, proteomic analysis can help to better understand the mechanisms underlying F(-) toxicity, even in low doses. Copyright © 2010 Wiley Periodicals, Inc.

Proteomics Analysis Reveals Abnormal Electron Transport and Excessive Oxidative Stress Cause Mitochondrial Dysfunction in Placental Tissues of Early-Onset Preeclampsia.

PubMed

Xu, Zhongwei; Jin, Xiaohan; Cai, Wei; Zhou, Maobin; Shao, Ping; Yang, Zhen; Fu, Rong; Cao, Jin; Liu, Yan; Yu, Fang; Fan, Rong; Zhang, Yan; Zou, Shuang; Zhou, Xin; Yang, Ning; Chen, Xu; Li, Yuming

2018-04-20

Early-onset preeclampsia (EOS-PE) refers to preeclampsia that occurred before 34 gestation weeks. This study is conducted to explore the relationship between mitochondrial dysfunction and the pathogenesis of EOS-PE using proteomic strategy. To identify altering expressed mitochondrial proteins between severe EOS-PE and healthy pregnancies, enrichment of mitochondria coupled with iTRAQ-based quantitative proteomic method is performed. Immunohistochemistry (IHC) and western blot are performed to detect the alteration of changing expression proteins, and confirmed the accuracy of proteomic results. A total of 1372 proteins were quantified and 132 altering expressed proteins were screened, including 86 downregulated expression proteins and 46 upregulated expression proteins (p < 0.05). Bioinformatics analysis showed that differentially expressed proteins participated in numerous biological processes, including oxidation-reduction process, respiratory electron transport chain, and oxidative phosphorylation. Especially, mitochondria-related molecules, PRDX2, PARK7, BNIP3, BCL2, PDHA1, SUCLG1, ACADM, and NDUFV1, are involved in energy-production process in the matrix and membrane of mitochondria. Results of the experiment show that abnormal electron transport, excessive oxidative stress, and mitochondrion disassembly might be the main cause of mitochondrial dysfunction, and is related to the pathogenesis of EOS-PE. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Quantitative Proteomics by Metabolic Labeling of Model Organisms*

PubMed Central

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

2010-01-01

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

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.

Bovine milk proteome: Quantitative changes in normal milk exosomes, milk fat globule membranes and whey proteomes resulting from Staphylococcus aureus mastitis

USDA-ARS?s Scientific Manuscript database

Knowledge of milk protein composition/expression in healthy cows and cows with mastitis will provide information important for the dairy food industry, mammary biology and immune function in the mammary gland. To facilitate maximum protein discovery, milk was fractioned into whey, milk fat globule ...

Proteomic dataset of the sea urchin Paracentrotus lividus adhesive organs and secreted adhesive.

PubMed

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

2016-06-01

Sea urchins have specialized adhesive organs called tube feet, which mediate strong but reversible adhesion. Tube feet are composed by a disc, producing adhesive and de-adhesive secretions for substratum attachment, and a stem for movement. After detachment the secreted adhesive remains bound to the substratum as a footprint. Recently, a label-free quantitative proteomic approach coupled with the latest mass-spectrometry technology was used to analyze the differential proteome of Paracentrotus lividus adhesive organ, comparing protein expression levels in the tube feet adhesive part (the disc) versus the non-adhesive part (the stem), and also to profile the proteome of the secreted adhesive (glue). This data article contains complementary figures and results related to the research article "Deciphering the molecular mechanisms underlying sea urchin reversible adhesion: a quantitative proteomics approach" (Lebesgue et al., 2016) [1]. Here we provide a dataset of 1384 non-redundant proteins, their fragmented peptides and expression levels, resultant from the analysis of the tube feet differential proteome. Of these, 163 highly over-expressed tube feet disc proteins (>3-fold), likely representing the most relevant proteins for sea urchin reversible adhesion, were further annotated in order to determine the potential functions. In addition, we provide a dataset of 611 non-redundant proteins identified in the secreted adhesive proteome, as well as their functional annotation and grouping in 5 major protein groups related with adhesive exocytosis, and microbial protection. This list was further analyzed to identify the most abundant protein groups and pinpoint putative adhesive proteins, such as Nectin, the most abundant adhesive protein in sea urchin glue. The obtained data uncover the key proteins involved in sea urchins reversible adhesion, representing a step forward to the development of new wet-effective bio-inspired adhesives.

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

Venom-gland transcriptomics and venom proteomics of the black-back scorpion (Hadrurus spadix) reveal detectability challenges and an unexplored realm of animal toxin diversity.

PubMed

Rokyta, Darin R; Ward, Micaiah J

2017-03-15

The order Scorpiones is one of the most ancient and diverse lineages of venomous animals, having originated approximately 430 million years ago and diversified into 14 extant families. Although partial venom characterizations have been described for numerous scorpion species, we provided the first quantitative transcriptome/proteome comparison for a scorpion species using single-animal approaches. We sequenced the venom-gland transcriptomes of a male and female black-back scorpion (Hadrurus spadix) from the family Caraboctonidae using the Illumina sequencing platform and conducted independent quantitative mass-spectrometry analyses of their venoms. We identified 79 proteomically confirmed venom proteins, an additional 69 transcripts with homology to toxins from other species, and 596 nontoxin proteins expressed at high levels in the venom glands. The venom of H. spadix was rich in antimicrobial peptides, K + -channel toxins, and several classes of peptidases. However, the most diverse and one of the most abundant classes of putative toxins could not be assigned even a tentative functional role on the basis of homology, indicating that this venom contained a wealth of previously unexplored animal toxin diversity. We found good agreement between both transcriptomic and proteomic abundances across individuals, but transcriptomic and proteomic abundandances differed substantially within each individual. Small peptide toxins such as K + -channel toxins and antimicrobial peptides proved challenging to detect proteomically, at least in part due to the significant proteolytic processing involved in their maturation. In addition, we found a significant tendency for our proteomic approach to overestimate the abundances of large putative toxins and underestimate the abundances of smaller toxins. Copyright © 2017 Elsevier Ltd. All rights reserved.

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

PubMed Central

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

2012-01-01

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

Proteomic dataset of the sea urchin Paracentrotus lividus adhesive organs and secreted adhesive

PubMed Central

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

2016-01-01

Sea urchins have specialized adhesive organs called tube feet, which mediate strong but reversible adhesion. Tube feet are composed by a disc, producing adhesive and de-adhesive secretions for substratum attachment, and a stem for movement. After detachment the secreted adhesive remains bound to the substratum as a footprint. Recently, a label-free quantitative proteomic approach coupled with the latest mass-spectrometry technology was used to analyze the differential proteome of Paracentrotus lividus adhesive organ, comparing protein expression levels in the tube feet adhesive part (the disc) versus the non-adhesive part (the stem), and also to profile the proteome of the secreted adhesive (glue). This data article contains complementary figures and results related to the research article “Deciphering the molecular mechanisms underlying sea urchin reversible adhesion: a quantitative proteomics approach” (Lebesgue et al., 2016) [1]. Here we provide a dataset of 1384 non-redundant proteins, their fragmented peptides and expression levels, resultant from the analysis of the tube feet differential proteome. Of these, 163 highly over-expressed tube feet disc proteins (>3-fold), likely representing the most relevant proteins for sea urchin reversible adhesion, were further annotated in order to determine the potential functions. In addition, we provide a dataset of 611 non-redundant proteins identified in the secreted adhesive proteome, as well as their functional annotation and grouping in 5 major protein groups related with adhesive exocytosis, and microbial protection. This list was further analyzed to identify the most abundant protein groups and pinpoint putative adhesive proteins, such as Nectin, the most abundant adhesive protein in sea urchin glue. The obtained data uncover the key proteins involved in sea urchins reversible adhesion, representing a step forward to the development of new wet-effective bio-inspired adhesives. PMID:27182547

Proteomics for understanding miRNA biology

PubMed Central

Huang, Tai-Chung; Pinto, Sneha M.; Pandey, Akhilesh

2013-01-01

MicroRNAs (miRNAs) are small noncoding RNAs that play important roles in posttranscriptional regulation of gene expression. Mature miRNAs associate with the RNA interference silencing complex to repress mRNA translation and/or degrade mRNA transcripts. Mass spectrometry-based proteomics has enabled identification of several core components of the canonical miRNA processing pathway and their posttranslational modifications which are pivotal in miRNA regulatory mechanisms. The use of quantitative proteomic strategies has also emerged as a key technique for experimental identification of miRNA targets by allowing direct determination of proteins whose levels are altered because of translational suppression. This review focuses on the role of proteomics and labeling strategies to understand miRNA biology. PMID:23125164

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

PubMed Central

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

2015-01-01

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

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

DOE PAGES

Smith, Richard D.

2002-01-01

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

Diagnosis of major depressive disorder by combining multimodal information from heart rate dynamics and serum proteomics using machine-learning algorithm.

PubMed

Kim, Eun Young; Lee, Min Young; Kim, Se Hyun; Ha, Kyooseob; Kim, Kwang Pyo; Ahn, Yong Min

2017-06-02

Major depressive disorder (MDD) is a systemic and multifactorial disorder that involves abnormalities in multiple biochemical pathways and the autonomic nervous system. This study applied a machine-learning method to classify MDD and control groups by incorporating data from serum proteomic analysis and heart rate variability (HRV) analysis for the identification of novel peripheral biomarkers. The study subjects consisted of 25 drug-free female MDD patients and 25 age- and sex-matched healthy controls. First, quantitative serum proteome profiles were analyzed by liquid chromatography-tandem mass spectrometry using pooled serum samples from 10 patients and 10 controls. Next, candidate proteins were quantified with multiple reaction monitoring (MRM) in 50 subjects. We also analyzed 22 linear and nonlinear HRV parameters in 50 subjects. Finally, we identified a combined biomarker panel consisting of proteins and HRV indexes using a support vector machine with recursive feature elimination. A separation between MDD and control groups was achieved using five parameters (apolipoprotein B, group-specific component, ceruloplasmin, RMSSD, and SampEn) at 80.1% classification accuracy. A combination of HRV and proteomic data achieved better classification accuracy. A high classification accuracy can be achieved by combining multimodal information from heart rate dynamics and serum proteomics in MDD. Our approach can be helpful for accurate clinical diagnosis of MDD. Further studies using larger, independent cohorts are needed to verify the role of these candidate biomarkers for MDD diagnosis. Copyright © 2017 Elsevier Inc. All rights reserved.

Multivariate proteomic profiling identifies novel accessory proteins of coated vesicles

PubMed Central

Antrobus, Robin; Hirst, Jennifer; Bhumbra, Gary S.; Kozik, Patrycja; Jackson, Lauren P.; Sahlender, Daniela A.

2012-01-01

Despite recent advances in mass spectrometry, proteomic characterization of transport vesicles remains challenging. Here, we describe a multivariate proteomics approach to analyzing clathrin-coated vesicles (CCVs) from HeLa cells. siRNA knockdown of coat components and different fractionation protocols were used to obtain modified coated vesicle-enriched fractions, which were compared by stable isotope labeling of amino acids in cell culture (SILAC)-based quantitative mass spectrometry. 10 datasets were combined through principal component analysis into a “profiling” cluster analysis. Overall, 136 CCV-associated proteins were predicted, including 36 new proteins. The method identified >93% of established CCV coat proteins and assigned >91% correctly to intracellular or endocytic CCVs. Furthermore, the profiling analysis extends to less well characterized types of coated vesicles, and we identify and characterize the first AP-4 accessory protein, which we have named tepsin. Finally, our data explain how sequestration of TACC3 in cytosolic clathrin cages causes the severe mitotic defects observed in auxilin-depleted cells. The profiling approach can be adapted to address related cell and systems biological questions. PMID:22472443

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.

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

PubMed

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

2014-05-30

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

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

PubMed

Song, Jun; Du, Lina; Li, Li; Kalt, Wilhelmina; Palmer, Leslie Campbell; Fillmore, Sherry; Zhang, Ying; Zhang, ZhaoQi; Li, XiHong

2015-06-03

To better understand the regulation of flavonoid and anthocyanin biosynthesis, a targeted quantitative proteomic investigation employing LC-MS with multiple reaction monitoring was conducted on two strawberry cultivars at three ripening stages. This quantitative proteomic workflow was improved through an OFFGEL electrophoresis to fractionate peptides from total protein digests. A total of 154 peptide transitions from 47 peptides covering 21 proteins and isoforms related to anthocyanin biosynthesis were investigated. The normalized protein abundance, which was measured using isotopically-labeled standards, was significantly changed concurrently with increased anthocyanin content and advanced fruit maturity. The protein abundance of phenylalanine ammonia-lyase; anthocyanidin synthase, chalcone isomerase; flavanone 3-hydroxylase; dihydroflavonol 4-reductase, UDP-glucose:flavonoid-3-O-glucosyltransferase, cytochrome c and cytochrome C oxidase subunit 2, was all significantly increased in fruit of more advanced ripeness. An interaction between cultivar and maturity was also shown with respect to chalcone isomerase. The good correlation between protein abundance and anthocyanin content suggested that a metabolic control point may exist for anthocyanin biosynthesis. This research provides insights into the process of anthocyanin formation in strawberry fruit at the level of protein concentration and reveals possible candidates in the regulation of anthocyanin formation during fruit ripening. To gain insight into the molecular mechanisms contributing to flavonoids and anthocyanin biosynthesis and regulation of strawberry fruit during ripening is challenging due to limited molecular biology tools and established hypothesis. Our targeted proteomic approach employing LC-MS/MS analysis and MRM technique to quantify proteins in relation to flavonoids and anthocyanin biosynthesis and regulation in strawberry fruit during fruit ripening is novel. The identification of peptides and proteins provided reliable design and validation of quantitative approaches using SRM on targeted proteins proposed involved in strawberry fruit. Our data revealed the identifying candidate proteins and their quantitative changes in relation to fruit ripening and flavonoids and anthocyanin biosynthesis and regulation. More importantly, this quantitative proteomic data is also compared with chemical analysis to reveal possible control levels of this important quality trait. Although, MRM approach is not new in plant biology research, the application has been very rare. This is the first systematic multi-targeted interrogation of the possible regulation of entire pathway of flavonoids and anthocyanin biosynthesis in strawberry fruit at different ripening stages using quantitative MRM technique on mass spectrometry. Our results demonstrate the power of targeted quantitative mass spectrometry data for analysis of proteins in biological regulation. These results indicate that distinct and diverse control of flavonoids and anthocyanin biosynthesis mechanisms at metabolism and proteins levels. This important and complementary knowledge will be useful for systematically characterizing the flavonoids and anthocyanin biosynthesis pathway of any fruit/plant species. Copyright © 2015. Published by Elsevier B.V.

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

PubMed

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

2016-04-29

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

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

PubMed Central

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

2014-01-01

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

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

PubMed

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

2013-12-06

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

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

PubMed

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

2017-12-01

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

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.

Population-specific plasma proteomes of marine and freshwater three-spined sticklebacks (Gasterosteus aculeatus).

PubMed

Kültz, Dietmar; Li, Johnathon; Zhang, Xuezhen; Villarreal, Fernando; Pham, Tuan; Paguio, Darlene

2015-12-01

Molecular phenotypes that distinguish resident marine (Bodega Harbor) from landlocked freshwater (FW, Lake Solano) three-spined sticklebacks were revealed by label-free quantitative proteomics. Secreted plasma proteins involved in lipid transport, blood coagulation, proteolysis, plasminogen-activating cascades, extracellular stimulus responses, and immunity are most abundant in this species. Globulins and albumins are much less abundant than in mammalian plasma. Unbiased quantitative proteome profiling identified 45 highly population-specific plasma proteins. Population-specific abundance differences were validated by targeted proteomics based on data-independent acquisition. Gene ontology enrichment analyses and known functions of population-specific plasma proteins indicate enrichment of processes controlling cell adhesion, tissue remodeling, proteolytic processing, and defense signaling in marine sticklebacks. Moreover, fetuin B and leukocyte cell derived chemotaxin 2 are much more abundant in marine fish. These proteins promote bone morphogenesis and likely contribute to population-specific body armor differences. Plasma proteins enriched in FW fish promote translation, heme biosynthesis, and lipid transport, suggesting a greater presence of plasma microparticles. Many prominent population-specific plasma proteins (e.g. apoptosis-associated speck-like protein containing a CARD) lack any homolog of known function or adequate functional characterization. Their functional characterization and the identification of population-specific environmental contexts and selective pressures that cause plasma proteome diversification are future directions emerging from this study. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

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

PubMed

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

2015-01-01

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

A tutorial in displaying mass spectrometry-based proteomic data using heat maps.

PubMed

Key, Melissa

2012-01-01

Data visualization plays a critical role in interpreting experimental results of proteomic experiments. Heat maps are particularly useful for this task, as they allow us to find quantitative patterns across proteins and biological samples simultaneously. The quality of a heat map can be vastly improved by understanding the options available to display and organize the data in the heat map. This tutorial illustrates how to optimize heat maps for proteomics data by incorporating known characteristics of the data into the image. First, the concepts used to guide the creating of heat maps are demonstrated. Then, these concepts are applied to two types of analysis: visualizing spectral features across biological samples, and presenting the results of tests of statistical significance. For all examples we provide details of computer code in the open-source statistical programming language R, which can be used for biologists and clinicians with little statistical background. Heat maps are a useful tool for presenting quantitative proteomic data organized in a matrix format. Understanding and optimizing the parameters used to create the heat map can vastly improve both the appearance and the interoperation of heat map data.

Deciphering of the Human Interferon-Regulated Proteome by Mass Spectrometry-Based Quantitative Analysis Reveals Extent and Dynamics of Protein Induction and Repression

PubMed Central

Megger, Dominik A.; Philipp, Jos; Le-Trilling, Vu Thuy Khanh; Sitek, Barbara; Trilling, Mirko

2017-01-01

Interferons (IFNs) are pleotropic cytokines secreted upon encounter of pathogens and tumors. Applying their antipathogenic, antiproliferative, and immune stimulatory capacities, recombinant IFNs are frequently prescribed as drugs to treat different diseases. IFNs act by changing the gene expression profile of cells. Due to characteristics such as rapid gene induction and signaling, IFNs also represent prototypical model systems for various aspects of biomedical research (e.g., signal transduction). In regard to the signaling and activated promoters, IFNs can be subdivided into two groups. Here, alterations of the cellular proteome of human cells treated with IFNα and IFNγ were elucidated in a time-resolved manner by quantitative proteome analysis. The majority of protein regulations were strongly IFN type and time dependent. In addition to the expected upregulation of IFN-responsive proteins, an astonishing number of proteins became profoundly repressed especially by IFNγ. Thus, our comprehensive analysis revealed important insights into the human IFN-regulated proteome and its dynamics of protein induction and repression. Interestingly, the new class of IFN-repressed genes comprises known host factors for highly relevant pathogens such as HIV, dengue virus, and hepatitis C virus. PMID:28959263

Proteomic Analyses of the Effects of Drugs of Abuse on Monocyte-Derived Mature Dendritic Cells

PubMed Central

Reynolds, Jessica L.; Mahajan, Supriya D.; Aalinkeel, Ravikunar; Nair, B.; Sykes, Donald E.; Schwartz, Stanley A.

2010-01-01

Drug abuse has become a global health concern. Understanding how drug abuse modulates the immune system and how the immune system responds to pathogens associated with drug abuse, such hepatitis C virus (HCV) and human immunodeficiency virus (HIV-1), can be assessed by an integrated approach comparing proteomic analyses and quantitation of gene expression. Two-dimensional (2D) difference gel electrophoresis was used to determine the molecular mechanisms underlying the proteomic changes that alter normal biological processes when monocyte-derived mature dendritic cells were treated with cocaine or methamphetamine. Both drugs differentially regulated the expression of several functional classes of proteins including those that modulate apoptosis, protein folding, protein kinase activity, and metabolism and proteins that function as intracellular signal transduction molecules. Proteomic data were validated using a combination of quantitative, real-time PCR and Western blot analyses. These studies will help to identify the molecular mechanisms, including the expression of several functionally important classes of proteins that have emerged as potential mediators of pathogenesis. These proteins may predispose immunocompetent cells, including dendritic cells, to infection with viruses such as HCV and HIV-1, which are associated with drug abuse. PMID:19811410

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

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

PubMed

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

2015-08-01

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

Deciphering of the Human Interferon-Regulated Proteome by Mass Spectrometry-Based Quantitative Analysis Reveals Extent and Dynamics of Protein Induction and Repression.

PubMed

Megger, Dominik A; Philipp, Jos; Le-Trilling, Vu Thuy Khanh; Sitek, Barbara; Trilling, Mirko

2017-01-01

Interferons (IFNs) are pleotropic cytokines secreted upon encounter of pathogens and tumors. Applying their antipathogenic, antiproliferative, and immune stimulatory capacities, recombinant IFNs are frequently prescribed as drugs to treat different diseases. IFNs act by changing the gene expression profile of cells. Due to characteristics such as rapid gene induction and signaling, IFNs also represent prototypical model systems for various aspects of biomedical research (e.g., signal transduction). In regard to the signaling and activated promoters, IFNs can be subdivided into two groups. Here, alterations of the cellular proteome of human cells treated with IFNα and IFNγ were elucidated in a time-resolved manner by quantitative proteome analysis. The majority of protein regulations were strongly IFN type and time dependent. In addition to the expected upregulation of IFN-responsive proteins, an astonishing number of proteins became profoundly repressed especially by IFNγ. Thus, our comprehensive analysis revealed important insights into the human IFN-regulated proteome and its dynamics of protein induction and repression. Interestingly, the new class of IFN-repressed genes comprises known host factors for highly relevant pathogens such as HIV, dengue virus, and hepatitis C virus.

The quantitative and condition-dependent Escherichia coli proteome

PubMed Central

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

2016-01-01

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

Parasites, proteomes and systems: has Descartes' clock run out of time?

PubMed

Wastling, J M; Armstrong, S D; Krishna, R; Xia, D

2012-08-01

Systems biology aims to integrate multiple biological data types such as genomics, transcriptomics and proteomics across different levels of structure and scale; it represents an emerging paradigm in the scientific process which challenges the reductionism that has dominated biomedical research for hundreds of years. Systems biology will nevertheless only be successful if the technologies on which it is based are able to deliver the required type and quality of data. In this review we discuss how well positioned is proteomics to deliver the data necessary to support meaningful systems modelling in parasite biology. We summarise the current state of identification proteomics in parasites, but argue that a new generation of quantitative proteomics data is now needed to underpin effective systems modelling. We discuss the challenges faced to acquire more complete knowledge of protein post-translational modifications, protein turnover and protein-protein interactions in parasites. Finally we highlight the central role of proteome-informatics in ensuring that proteomics data is readily accessible to the user-community and can be translated and integrated with other relevant data types.

Halobacterium salinarum NRC-1 PeptideAtlas: strategies for targeted proteomics

PubMed Central

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

2009-01-01

The relatively small numbers of proteins and fewer possible posttranslational modifications in microbes provides a unique opportunity to comprehensively characterize their dynamic proteomes. We have constructed a Peptide Atlas (PA) for 62.7% of the predicted proteome of the extremely halophilic archaeon Halobacterium salinarum NRC-1 by compiling approximately 636,000 tandem mass spectra from 497 mass spectrometry runs in 88 experiments. Analysis of the PA with respect to biophysical properties of constituent peptides, functional properties of parent proteins of detected peptides, and performance of different mass spectrometry approaches has helped highlight plausible strategies for improving proteome coverage and selecting signature peptides for targeted proteomics. Notably, discovery of a significant correlation between absolute abundances of mRNAs and proteins has helped identify low abundance of proteins as the major limitation in peptide detection. Furthermore we have discovered that iTRAQ labeling for quantitative proteomic analysis introduces a significant bias in peptide detection by mass spectrometry. Therefore, despite identifying at least one proteotypic peptide for almost all proteins in the PA, a context-dependent selection of proteotypic peptides appears to be the most effective approach for targeted proteomics. PMID:18652504

Parasites, proteomes and systems: has Descartes’ clock run out of time?

PubMed Central

WASTLING, J. M.; ARMSTRONG, S. D.; KRISHNA, R.; XIA, D.

2012-01-01

SUMMARY Systems biology aims to integrate multiple biological data types such as genomics, transcriptomics and proteomics across different levels of structure and scale; it represents an emerging paradigm in the scientific process which challenges the reductionism that has dominated biomedical research for hundreds of years. Systems biology will nevertheless only be successful if the technologies on which it is based are able to deliver the required type and quality of data. In this review we discuss how well positioned is proteomics to deliver the data necessary to support meaningful systems modelling in parasite biology. We summarise the current state of identification proteomics in parasites, but argue that a new generation of quantitative proteomics data is now needed to underpin effective systems modelling. We discuss the challenges faced to acquire more complete knowledge of protein post-translational modifications, protein turnover and protein-protein interactions in parasites. Finally we highlight the central role of proteome-informatics in ensuring that proteomics data is readily accessible to the user-community and can be translated and integrated with other relevant data types. PMID:22828391

Immune Repertoire after Immunization As Seen by Next-Generation Sequencing and Proteomics

PubMed Central

VanDuijn, Martijn M.; Dekker, Lennard J.; van IJcken, Wilfred F. J.; Sillevis Smitt, Peter A. E.; Luider, Theo M.

2017-01-01

The immune system produces a diverse repertoire of immunoglobulins in response to foreign antigens. During B-cell development, VDJ recombination and somatic mutations generate diversity, whereas selection processes remove it. Using both proteomic and NGS approaches, we characterized the immune repertoires in groups of rats after immunization with purified antigens. Proteomics and NGS data on the repertoire are in qualitative agreement, but did show quantitative differences that may relate to differences between the biological niches that were sampled for these approaches. Both methods contributed complementary information in the characterization of the immune repertoire. It was found that the immune repertoires resulting from each antigen had many similarities that allowed samples to cluster together, and that mutated immunoglobulin peptides were shared among animals with a response to the same antigen significantly more than for different antigens. However, the number of shared sequences decreased in a log-linear fashion relative to the number of animals that share them, which may affect future applications. A phylogenetic analysis on the NGS reads showed that reads from different individuals immunized with the same antigen populated distinct branches of the phylogram, an indication that the repertoire had converged. Also, similar mutation patterns were found in branches of the phylogenetic tree that were associated with antigen-specific immunoglobulins through proteomics data. Thus, data from different analysis methods and different experimental platforms show that the immunoglobulin repertoires of immunized animals have overlapping and converging features. With additional research, this may enable interesting applications in biotechnology and clinical diagnostics. PMID:29085363

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

PubMed

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

2016-09-01

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

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

PubMed

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

2008-09-01

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

Proteomic analysis of single mammalian cells enabled by microfluidic nanodroplet sample preparation and ultrasensitive nanoLC-MS.

PubMed

Zhu, Ying; Clair, Geremy; Chrisler, William; Shen, Yufeng; Zhao, Rui; Shukla, Anil; Moore, Ronald; Misra, Ravi; Pryhuber, Gloria; Smith, Richard; Ansong, Charles; Kelly, Ryan T

2018-05-24

We report on the quantitative proteomic analysis of single mammalian cells. Fluorescence-activated cell sorting was employed to deposit cells into a newly developed nanodroplet sample processing chip, after which samples were analysed by ultrasensitive nanoLC-MS. An average of ~670 protein groups were confidently identified from single HeLa cells, which is a far greater level of proteome coverage for single cells than has been previously reported. We demonstrate that the single cell proteomics platform can be used to differentiate cell types from enzyme-dissociated human lung primary cells and identify specific protein markers for epithelial and mesenchymal cells. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

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

PubMed Central

2015-01-01

Atropine, a muscarinic antagonist, is known to inhibit myopia progression in several animal models and humans. However, the mode of action is not established yet. In this study, we compared quantitative iTRAQ proteomic analysis in the retinas collected from control and lens-induced myopic (LIM) mouse eyes treated with atropine. The myopic group received a (−15D) spectacle lens over the right eye on postnatal day 10 with or without atropine eye drops starting on postnatal day 24. Axial length was measured by optical low coherence interferometry (OLCI), AC-Master, and refraction was measured by automated infrared photorefractor at postnatal 24, 38, and 52 days. Retinal tissue samples were pooled from six eyes for each group. The experiments were repeated twice, and technical replicates were also performed for liquid chromatography–tandem mass spectrometry (LC–MS/MS) analysis. MetaCore was used to perform protein profiling for pathway analysis. We identified a total of 3882 unique proteins with <1% FDR by analyzing the samples in replicates for two independent experiments. This is the largest number of mouse retina proteome reported to date. Thirty proteins were found to be up-regulated (ratio for myopia/control > global mean ratio + 1 standard deviation), and 28 proteins were down-regulated (ratio for myopia/control < global mean ratio - 1 standard deviation) in myopic eyes as compared with control retinas. Pathway analysis using MetaCore revealed regulation of γ-aminobutyric acid (GABA) levels in the myopic eyes. Detailed analysis of the quantitative proteomics data showed that the levels of GABA transporter 1 (GAT-1) were elevated in myopic retina and significantly reduced after atropine treatment. These results were further validated with immunohistochemistry and Western blot analysis. In conclusion, this study provides a comprehensive quantitative proteomic analysis of atropine-treated mouse retina and suggests the involvement of GABAergic signaling in the antimyopic effects of atropine in mouse eyes. The GABAergic transmission in the neural retina plays a pivotal role in the maintenance of axial eye growth in mammals. PMID:25211393

Quantitative Proteomic Analysis of Serum Exosomes from Patients with Locally Advanced Pancreatic Cancer Undergoing Chemoradiotherapy.

PubMed

An, Mingrui; Lohse, Ines; Tan, Zhijing; Zhu, Jianhui; Wu, Jing; Kurapati, Himabindu; Morgan, Meredith A; Lawrence, Theodore S; Cuneo, Kyle C; Lubman, David M

2017-04-07

Pancreatic cancer is the third leading cause of cancer-related death in the USA. Despite extensive research, minimal improvements in patient outcomes have been achieved. Early identification of treatment response and metastasis would be valuable to determine the appropriate therapeutic course for patients. In this work, we isolated exosomes from the serum of 10 patients with locally advanced pancreatic cancer at serial time points over a course of therapy, and quantitative analysis was performed using the iTRAQ method. We detected approximately 700-800 exosomal proteins per sample, several of which have been implicated in metastasis and treatment resistance. We compared the exosomal proteome of patients at different time points during treatment to healthy controls and identified eight proteins that show global treatment-specific changes. We then tested the effect of patient-derived exosomes on the migration of tumor cells and found that patient-derived exosomes, but not healthy controls, induce cell migration, supporting their role in metastasis. Our data show that exosomes can be reliably extracted from patient serum and analyzed for protein content. The differential loading of exosomes during a course of therapy suggests that exosomes may provide novel insights into the development of treatment resistance and metastasis.

Dynamic quantitative proteomics characterization of TNF-α-induced necroptosis.

PubMed

Wang, Yang; Huang, Zhi-Hao; Li, Yang-Jia; He, Gui-Wei; Yu, Ru-Yuan; Yang, Jie; Liu, Wan-Ting; Li, Bin; He, Qing-Yu

2016-12-01

Emerging evidence suggested that necroptosis has essential functions in many human inflammatory diseases, but the molecular mechanisms of necroptosis remain unclear. Here, we employed SILAC quantitatively dynamic proteomics to compare the protein changes during TNF-α-induced necroptosis at different time points in murine fibrosarcoma L929 cells with caspase-8 deficiency, and then performed the systematical analysis on the signaling networks involved in the progress using bioinformatics methods. Our results showed that a total of 329, 421 and 378 differentially expressed proteins were detected at three stages of necroptosis, respectively. Gene ontology and ingenuity pathway analysis (IPA) revealed that the proteins regulated at early stages of necroptosis (2, 6 h) were mainly involved in mitochondria dysfunction, oxidative phosphorylation and Nrf-2 signaling, while the expression levels of the proteins related to ubiquitin, Nrf-2, and NF-κB pathways were found to have changes at last stages of necroptosis (6, 18 h). Taken together, we demonstrated for the first time that dysfunction of mitochondria and ubiquitin-proteasome signaling contributed to the initiation and execution of necroptosis. These findings may provide clues for the identification of important regulators in necroptosis and the development of novel therapeutic strategies for the related diseases.

Proteomics approaches advance our understanding of plant self-incompatibility response.

PubMed

Sankaranarayanan, Subramanian; Jamshed, Muhammad; Samuel, Marcus A

2013-11-01

Self-incompatibility (SI) in plants is a genetic mechanism that prevents self-fertilization and promotes out-crossing needed to maintain genetic diversity. SI has been classified into two broad categories: the gametophytic self-incompatibility (GSI) and the sporophytic self-incompatibility (SSI) based on the genetic mechanisms involved in 'self' pollen rejection. Recent proteomic approaches to identify potential candidates involved in SI have shed light onto a number of previously unidentified mechanisms required for SI response. SI proteome research has progressed from the use of isoelectric focusing in early days to the latest third-generation technique of comparative isobaric tag for relative and absolute quantitation (iTRAQ) used in recent times. We will focus on the proteome-based approaches used to study self-incompatibility (GSI and SSI), recent developments in the field of incompatibility research with emphasis on SSI and future prospects of using proteomic approaches to study self-incompatibility.

Quantitative proteomic analysis of cultured skin fibroblast cells derived from patients with triglyceride deposit cardiomyovasculopathy

PubMed Central

2013-01-01

Background Triglyceride deposit cardiomyovasculopathy (TGCV) is a rare disease, characterized by the massive accumulation of triglyceride (TG) in multiple tissues, especially skeletal muscle, heart muscle and the coronary artery. TGCV is caused by mutation of adipose triglyceride lipase, which is an essential molecule for the hydrolysis of TG. TGCV is at high risk for skeletal myopathy and heart dysfunction, and therefore premature death. Development of therapeutic methods for TGCV is highly desirable. This study aims to discover specific molecules responsible for TGCV pathogenesis. Methods To identify differentially expressed proteins in TGCV patient cells, the stable isotope labeling with amino acids in cell culture (SILAC) method coupled with LC-MS/MS was performed using skin fibroblast cells derived from two TGCV patients and three healthy volunteers. Altered protein expression in TGCV cells was confirmed using the selected reaction monitoring (SRM) method. Microarray-based transcriptome analysis was simultaneously performed to identify changes in gene expression in TGCV cells. Results Using SILAC proteomics, 4033 proteins were quantified, 53 of which showed significantly altered expression in both TGCV patient cells. Twenty altered proteins were chosen and confirmed using SRM. SRM analysis successfully quantified 14 proteins, 13 of which showed the same trend as SILAC proteomics. The altered protein expression data set was used in Ingenuity Pathway Analysis (IPA), and significant networks were identified. Several of these proteins have been previously implicated in lipid metabolism, while others represent new therapeutic targets or markers for TGCV. Microarray analysis quantified 20743 transcripts, and 252 genes showed significantly altered expression in both TGCV patient cells. Ten altered genes were chosen, 9 of which were successfully confirmed using quantitative RT-PCR. Biological networks of altered genes were analyzed using an IPA search. Conclusions We performed the SILAC- and SRM-based identification-through-confirmation study using skin fibroblast cells derived from TGCV patients, and first identified altered proteins specific for TGCV. Microarray analysis also identified changes in gene expression. The functional networks of the altered proteins and genes are discussed. Our findings will be exploited to elucidate the pathogenesis of TGCV and discover clinically relevant molecules for TGCV in the near future. PMID:24360150

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

PubMed

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

2017-01-01

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

An introduction to statistical process control in research proteomics.

PubMed

Bramwell, David

2013-12-16

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

Multiplex N-terminome analysis of MMP-2 and MMP-9 substrate degradomes by iTRAQ-TAILS quantitative proteomics.

PubMed

Prudova, Anna; auf dem Keller, Ulrich; Butler, Georgina S; Overall, Christopher M

2010-05-01

Proteolysis is a major protein posttranslational modification that, by altering protein structure, affects protein function and, by truncating the protein sequence, alters peptide signatures of proteins analyzed by proteomics. To identify such modified and shortened protease-generated neo-N-termini on a proteome-wide basis, we developed a whole protein isobaric tag for relative and absolute quantitation (iTRAQ) labeling method that simultaneously labels and blocks all primary amines including protein N- termini and lysine side chains. Blocking lysines limits trypsin cleavage to arginine, which effectively elongates the proteolytically truncated peptides for improved MS/MS analysis and peptide identification. Incorporating iTRAQ whole protein labeling with terminal amine isotopic labeling of substrates (iTRAQ-TAILS) to enrich the N-terminome by negative selection of the blocked mature original N-termini and neo-N-termini has many advantages. It enables simultaneous characterization of the natural N-termini of proteins, their N-terminal modifications, and proteolysis product and cleavage site identification. Furthermore, iTRAQ-TAILS also enables multiplex N-terminomics analysis of up to eight samples and allows for quantification in MS2 mode, thus preventing an increase in spectral complexity and extending proteome coverage by signal amplification of low abundance proteins. We compared the substrate degradomes of two closely related matrix metalloproteinases, MMP-2 (gelatinase A) and MMP-9 (gelatinase B), in fibroblast secreted proteins. Among 3,152 unique N-terminal peptides identified corresponding to 1,054 proteins, we detected 201 cleavage products for MMP-2 and unexpectedly only 19 for the homologous MMP-9 under identical conditions. Novel substrates identified and biochemically validated include insulin-like growth factor binding protein-4, complement C1r component A, galectin-1, dickkopf-related protein-3, and thrombospondin-2. Hence, N-terminomics analyses using iTRAQ-TAILS links gelatinases with new mechanisms of action in angiogenesis and reveals unpredicted restrictions in substrate repertoires for these two very similar proteases.

Label-Free Quantitative Proteomics Identifies Novel Plasma Biomarkers for Distinguishing Pulmonary Tuberculosis and Latent Infection.

PubMed

Sun, Huishan; Pan, Liping; Jia, Hongyan; Zhang, Zhiguo; Gao, Mengqiu; Huang, Mailing; Wang, Jinghui; Sun, Qi; Wei, Rongrong; Du, Boping; Xing, Aiying; Zhang, Zongde

2018-01-01

The lack of effective differential diagnostic methods for active tuberculosis (TB) and latent infection (LTBI) is still an obstacle for TB control. Furthermore, the molecular mechanism behind the progression from LTBI to active TB has been not elucidated. Therefore, we performed label-free quantitative proteomics to identify plasma biomarkers for discriminating pulmonary TB (PTB) from LTBI. A total of 31 overlapping proteins with significant difference in expression level were identified in PTB patients ( n = 15), compared with LTBI individuals ( n = 15) and healthy controls (HCs, n = 15). Eight differentially expressed proteins were verified using western blot analysis, which was 100% consistent with the proteomics results. Statistically significant differences of six proteins were further validated in the PTB group compared with the LTBI and HC groups in the training set ( n = 240), using ELISA. Classification and regression tree (CART) analysis was employed to determine the ideal protein combination for discriminating PTB from LTBI and HC. A diagnostic model consisting of alpha-1-antichymotrypsin (ACT), alpha-1-acid glycoprotein 1 (AGP1), and E-cadherin (CDH1) was established and presented a sensitivity of 81.2% (69/85) and a specificity of 95.2% (80/84) in discriminating PTB from LTBI, and a sensitivity of 81.2% (69/85) and a specificity of 90.1% (64/81) in discriminating PTB from HCs. Additional validation was performed by evaluating the diagnostic model in blind testing set ( n = 113), which yielded a sensitivity of 75.0% (21/28) and specificity of 96.1% (25/26) in PTB vs. LTBI, 75.0% (21/28) and 92.3% (24/26) in PTB vs. HCs, and 75.0% (21/28) and 81.8% (27/33) in PTB vs. lung cancer (LC), respectively. This study obtained the plasma proteomic profiles of different M.TB infection statuses, which contribute to a better understanding of the pathogenesis involved in the transition from latent infection to TB activation and provide new potential diagnostic biomarkers for distinguishing PTB and LTBI.

Multiplex N-terminome Analysis of MMP-2 and MMP-9 Substrate Degradomes by iTRAQ-TAILS Quantitative Proteomics*

PubMed Central

Prudova, Anna; auf dem Keller, Ulrich; Butler, Georgina S.; Overall, Christopher M.

2010-01-01

Proteolysis is a major protein posttranslational modification that, by altering protein structure, affects protein function and, by truncating the protein sequence, alters peptide signatures of proteins analyzed by proteomics. To identify such modified and shortened protease-generated neo-N-termini on a proteome-wide basis, we developed a whole protein isobaric tag for relative and absolute quantitation (iTRAQ) labeling method that simultaneously labels and blocks all primary amines including protein N- termini and lysine side chains. Blocking lysines limits trypsin cleavage to arginine, which effectively elongates the proteolytically truncated peptides for improved MS/MS analysis and peptide identification. Incorporating iTRAQ whole protein labeling with terminal amine isotopic labeling of substrates (iTRAQ-TAILS) to enrich the N-terminome by negative selection of the blocked mature original N-termini and neo-N-termini has many advantages. It enables simultaneous characterization of the natural N-termini of proteins, their N-terminal modifications, and proteolysis product and cleavage site identification. Furthermore, iTRAQ-TAILS also enables multiplex N-terminomics analysis of up to eight samples and allows for quantification in MS2 mode, thus preventing an increase in spectral complexity and extending proteome coverage by signal amplification of low abundance proteins. We compared the substrate degradomes of two closely related matrix metalloproteinases, MMP-2 (gelatinase A) and MMP-9 (gelatinase B), in fibroblast secreted proteins. Among 3,152 unique N-terminal peptides identified corresponding to 1,054 proteins, we detected 201 cleavage products for MMP-2 and unexpectedly only 19 for the homologous MMP-9 under identical conditions. Novel substrates identified and biochemically validated include insulin-like growth factor binding protein-4, complement C1r component A, galectin-1, dickkopf-related protein-3, and thrombospondin-2. Hence, N-terminomics analyses using iTRAQ-TAILS links gelatinases with new mechanisms of action in angiogenesis and reveals unpredicted restrictions in substrate repertoires for these two very similar proteases. PMID:20305284

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

PubMed

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

2016-01-01

Powdery mildew (Pm), caused by Blumeria graminis f. sp. tritici (Bgt), is one of the most important crop diseases, causing severe economic losses to wheat production worldwide. However, there are few reports about the proteomic response to Bgt infection in resistant wheat. Hence, quantitative proteomic analysis of N9134, a resistant wheat line, was performed to explore the molecular mechanism of wheat in defense against Bgt. Comparing the leaf proteins of Bgt-inoculated N9134 with that of mock-inoculated controls, a total of 2182 protein-species were quantified by iTRAQ at 24, 48 and 72h postinoculation (hpi) with Bgt, of which 394 showed differential accumulation. These differentially accumulated protein-species (DAPs) mainly included pathogenesis-related (PR) polypeptides, oxidative stress responsive proteins and components involved in primary metabolic pathways. KEGG enrichment analysis showed that phenylpropanoid biosynthesis, phenylalanine metabolism and photosynthesis-antenna proteins were the key pathways in response to Bgt infection. InterProScan 5 and the Gibbs Motif Sampler cluster 394 DAPs into eight conserved motifs, which shared leucine repeats and histidine sites in the sequence motifs. Moreover, eight separate protein-protein interaction (PPI) networks were predicted from STRING database. This study provides a powerful platform for further exploration of the molecular mechanism underlying resistant wheat responding to Bgt. Powdery mildew, caused by Blumeria graminis f. sp. tritici (Bgt), is a destructive pathogenic disease in wheat-producing regions worldwide, resulting in severe yield reductions. Although many resistant wheat varieties have been cultivated, there are few reports about the proteomic response to Bgt infection in resistant wheat. Therefore, an iTRAQ-based quantitative proteomic analysis of a resistant wheat line (N9134) in response to Bgt infection has been performed. This paper provides new insights into the underlying molecular mechanism of wheat in response to Bgt. The proteomic analysis can significantly narrow the field of potential defense-related protein-species, and is conducive to recognize the critical or effector protein under Bgt infection more precisely. Taken together, large amounts of high-throughput data provide a powerful platform for further exploration of the molecular mechanism on wheat-Bgt interactions. Copyright © 2015 Elsevier B.V. All rights reserved.

Transitioning from Targeted to Comprehensive Mass Spectrometry Using Genetic Algorithms.

PubMed

Jaffe, Jacob D; Feeney, Caitlin M; Patel, Jinal; Lu, Xiaodong; Mani, D R

2016-11-01

Targeted proteomic assays are becoming increasingly popular because of their robust quantitative applications enabled by internal standardization, and they can be routinely executed on high performance mass spectrometry instrumentation. However, these assays are typically limited to 100s of analytes per experiment. Considerable time and effort are often expended in obtaining and preparing samples prior to targeted analyses. It would be highly desirable to detect and quantify 1000s of analytes in such samples using comprehensive mass spectrometry techniques (e.g., SWATH and DIA) while retaining a high degree of quantitative rigor for analytes with matched internal standards. Experimentally, it is facile to port a targeted assay to a comprehensive data acquisition technique. However, data analysis challenges arise from this strategy concerning agreement of results from the targeted and comprehensive approaches. Here, we present the use of genetic algorithms to overcome these challenges in order to configure hybrid targeted/comprehensive MS assays. The genetic algorithms are used to select precursor-to-fragment transitions that maximize the agreement in quantification between the targeted and the comprehensive methods. We find that the algorithm we used provided across-the-board improvement in the quantitative agreement between the targeted assay data and the hybrid comprehensive/targeted assay that we developed, as measured by parameters of linear models fitted to the results. We also found that the algorithm could perform at least as well as an independently-trained mass spectrometrist in accomplishing this task. We hope that this approach will be a useful tool in the development of quantitative approaches for comprehensive proteomics techniques. Graphical Abstract ᅟ.

Transitioning from Targeted to Comprehensive Mass Spectrometry Using Genetic Algorithms

NASA Astrophysics Data System (ADS)

Jaffe, Jacob D.; Feeney, Caitlin M.; Patel, Jinal; Lu, Xiaodong; Mani, D. R.

2016-11-01

Targeted proteomic assays are becoming increasingly popular because of their robust quantitative applications enabled by internal standardization, and they can be routinely executed on high performance mass spectrometry instrumentation. However, these assays are typically limited to 100s of analytes per experiment. Considerable time and effort are often expended in obtaining and preparing samples prior to targeted analyses. It would be highly desirable to detect and quantify 1000s of analytes in such samples using comprehensive mass spectrometry techniques (e.g., SWATH and DIA) while retaining a high degree of quantitative rigor for analytes with matched internal standards. Experimentally, it is facile to port a targeted assay to a comprehensive data acquisition technique. However, data analysis challenges arise from this strategy concerning agreement of results from the targeted and comprehensive approaches. Here, we present the use of genetic algorithms to overcome these challenges in order to configure hybrid targeted/comprehensive MS assays. The genetic algorithms are used to select precursor-to-fragment transitions that maximize the agreement in quantification between the targeted and the comprehensive methods. We find that the algorithm we used provided across-the-board improvement in the quantitative agreement between the targeted assay data and the hybrid comprehensive/targeted assay that we developed, as measured by parameters of linear models fitted to the results. We also found that the algorithm could perform at least as well as an independently-trained mass spectrometrist in accomplishing this task. We hope that this approach will be a useful tool in the development of quantitative approaches for comprehensive proteomics techniques.

Quantifying ubiquitin signaling.

PubMed

Ordureau, Alban; Münch, Christian; Harper, J Wade

2015-05-21

Ubiquitin (UB)-driven signaling systems permeate biology, and are often integrated with other types of post-translational modifications (PTMs), including phosphorylation. Flux through such pathways is dictated by the fractional stoichiometry of distinct modifications and protein assemblies as well as the spatial organization of pathway components. Yet, we rarely understand the dynamics and stoichiometry of rate-limiting intermediates along a reaction trajectory. Here, we review how quantitative proteomic tools and enrichment strategies are being used to quantify UB-dependent signaling systems, and to integrate UB signaling with regulatory phosphorylation events, illustrated with the PINK1/PARKIN pathway. A key feature of ubiquitylation is that the identity of UB chain linkage types can control downstream processes. We also describe how proteomic and enzymological tools can be used to identify and quantify UB chain synthesis and linkage preferences. The emergence of sophisticated quantitative proteomic approaches will set a new standard for elucidating biochemical mechanisms of UB-driven signaling systems. Copyright © 2015 Elsevier Inc. All rights reserved.

Two independent proteomic approaches provide a comprehensive analysis of the synovial fluid proteome response to Autologous Chondrocyte Implantation.

PubMed

Hulme, Charlotte H; Wilson, Emma L; Fuller, Heidi R; Roberts, Sally; Richardson, James B; Gallacher, Pete; Peffers, Mandy J; Shirran, Sally L; Botting, Catherine H; Wright, Karina T

2018-05-02

Autologous chondrocyte implantation (ACI) has a failure rate of approximately 20%, but it is yet to be fully understood why. Biomarkers are needed that can pre-operatively predict in which patients it is likely to fail, so that alternative or individualised therapies can be offered. We previously used label-free quantitation (LF) with a dynamic range compression proteomic approach to assess the synovial fluid (SF) of ACI responders and non-responders. However, we were able to identify only a few differentially abundant proteins at baseline. In the present study, we built upon these previous findings by assessing higher-abundance proteins within this SF, providing a more global proteomic analysis on the basis of which more of the biology underlying ACI success or failure can be understood. Isobaric tagging for relative and absolute quantitation (iTRAQ) proteomic analysis was used to assess SF from ACI responders (mean Lysholm improvement of 33; n = 14) and non-responders (mean Lysholm decrease of 14; n = 13) at the two stages of surgery (cartilage harvest and chondrocyte implantation). Differentially abundant proteins in iTRAQ and combined iTRAQ and LF datasets were investigated using pathway and network analyses. iTRAQ proteomic analysis confirmed our previous finding that there is a marked proteomic shift in response to cartilage harvest (70 and 54 proteins demonstrating ≥ 2.0-fold change and p < 0.05 between stages I and II in responders and non-responders, respectively). Further, it highlighted 28 proteins that were differentially abundant between responders and non-responders to ACI, which were not found in the LF study, 16 of which were altered at baseline. The differential expression of two proteins (complement C1s subcomponent and matrix metalloproteinase 3) was confirmed biochemically. Combination of the iTRAQ and LF proteomic datasets generated in-depth SF proteome information that was used to generate interactome networks representing ACI success or failure. Functional pathways that are dysregulated in ACI non-responders were identified, including acute-phase response signalling. Several candidate biomarkers for baseline prediction of ACI outcome were identified. A holistic overview of the SF proteome in responders and non-responders to ACI  has been profiled, providing a better understanding of the biological pathways underlying clinical outcome, particularly the differential response to cartilage harvest in non-responders.

Plasma proteomic changes during hypothermic and normothermic cardiopulmonary bypass in aortic surgeries

PubMed Central

ODA, TEIJI; YAMAGUCHI, AKANE; YOKOYAMA, MASAO; SHIMIZU, KOJI; TOYOTA, KOSAKU; NIKAI, TETSURO; MATSUMOTO, KEN-ICHI

2014-01-01

Deep hypothermic circulatory arrest (DHCA) is a protective method against brain ischemia in aortic surgery. However, the possible effects of DHCA on the plasma proteins remain to be determined. In the present study, we used novel high-throughput technology to compare the plasma proteomes during DHCA (22°C) with selective cerebral perfusion (SCP, n=7) to those during normothermic cardiopulmonary bypass (CPB, n=7). Three plasma samples per patient were obtained during CPB: T1, prior to cooling; T2, during hypothermia; T3, after rewarming for the DHCA group and three corresponding points for the normothermic group. A proteomic analysis was performed using isobaric tag for relative and absolute quantification (iTRAQ) labeling tandem mass spectrometry to assess quantitative protein changes. In total, the analysis identified 262 proteins. The bioinformatics analysis revealed a significant upregulation of complement activation at T2 in normothermic CPB, which was suppressed in DHCA. These findings were confirmed by the changes of the terminal complement complex (SC5b-9) levels. At T3, however, the level of SC5b-9 showed a greater increase in DHCA compared to normothermic CPB, while 48 proteins were significantly downregulated in DHCA. The results demonstrated that DHCA and rewarming potentially exert a significant effect on the plasma proteome in patients undergoing aortic surgery. PMID:25050567

Lack of β, β-carotene -9’, 10’-oxygenase 2 leads to hepatic mitochondrial dysfunction and cellular oxidative stress in mice

PubMed Central

Wu, Lei; Guo, Xin; Hartson, Steven D.; Davis, Mary Abby; He, Hui; Medeiros, Denis M.; Wang, Weiqun; Clarke, Stephen L.; Lucas, Edralin; Smith, Brenda J.; von Lintig, Johannes; Lin, Dingbo

2017-01-01

Scope β,β-carotene-9’,10’-dioxygenase 2 (BCO2) is a carotenoid cleavage enzyme localized to the inner mitochondrial membrane in mammals. This study was aimed to assess the impact of genetic ablation of BCO2 on hepatic oxidative stress through mitochondrial function in mice. Methods and Results Liver samples from 6 week old male BCO2−/− knockout (KO) and isogenic wild-type (WT) mice were subjected to proteomics and functional activity assays. Compared to the WT, KO mice consumed more food (by 18 %) yet displayed significantly lower body weight (by 12 %). Mitochondrial proteomic results demonstrated that loss of BCO2 was associated with quantitative changes of the mitochondrial proteome mainly shown by suppressed expression of enzymes and/or proteins involved in fatty acid β–oxidation, the tricarboxylic acid cycle, and the electron transport chain (ETC). The mitochondrial basal respiratory rate, proton leak, and ETC complex II capacity were significantly elevated in the livers of KO compared to WT mice. Moreover, elevated reactive oxygen species and increased mitochondrial protein carbonylation were also demonstrated in liver of KO mice. Conclusions Loss of BCO2 induces mitochondrial hyperactivation, mitochondrial stress and changes of the mitochondrial proteome, leading to mitochondrial energy insufficiency. BCO2 appears to be critical for proper hepatic mitochondrial function. PMID:27991717

Consistency of the Proteome in Primary Human Keratinocytes With Respect to Gender, Age, and Skin Localization*

PubMed Central

Sprenger, Adrian; Weber, Sebastian; Zarai, Mostafa; Engelke, Rudolf; Nascimento, Juliana M.; Gretzmeier, Christine; Hilpert, Martin; Boerries, Melanie; Has, Cristina; Busch, Hauke; Bruckner-Tuderman, Leena; Dengjel, Jörn

2013-01-01

Keratinocytes account for 95% of all cells of the epidermis, the stratified squamous epithelium forming the outer layer of the skin, in which a significant number of skin diseases takes root. Immortalized keratinocyte cell lines are often used as research model systems providing standardized, reproducible, and homogenous biological material. Apart from that, primary human keratinocytes are frequently used for medical studies because the skin provides an important route for drug administration and is readily accessible for biopsies. However, comparability of these cell systems is not known. Cell lines may undergo phenotypic shifts and may differ from the in vivo situation in important aspects. Primary cells, on the other hand, may vary in biological functions depending on gender and age of the donor and localization of the biopsy specimen. Here we employed metabolic labeling in combination with quantitative mass spectrometry-based proteomics to assess A431 and HaCaT cell lines for their suitability as model systems. Compared with cell lines, comprehensive profiling of the primary human keratinocyte proteome with respect to gender, age, and skin localization identified an unexpected high proteomic consistency. The data were analyzed by an improved ontology enrichment analysis workflow designed for the study of global proteomics experiments. It enables a quick, comprehensive and unbiased overview of altered biological phenomena and links experimental data to literature. We guide through our workflow, point out its advantages compared with other methods and apply it to visualize differences of cell lines compared with primary human keratinocytes. PMID:23722187

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.

Global proteomic analysis of two tick-borne emerging zoonotic agents: Anaplasma phagocytophilum and Ehrlichia chaffeensis

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

Lin, Mingqun ..; Kikuchi, Takane; Brewer, Heather M.

2011-02-17

Anaplasma phagocytophilum and Ehrlichia chaffeensis are obligatory intracellular {alpha}-proteobacteria that infect human leukocytes and cause potentially fatal emerging zoonoses. In the present study, we determined global protein expression profiles of these bacteria cultured in the human promyelocytic leukemia cell line, HL-60. Mass spectrometric (MS) analyses identified a total of 1,212 A. phagocytophilum and 1,021 E. chaffeensis proteins, representing 89.3 and 92.3% of the predicted bacterial proteomes, respectively. Nearly all bacterial proteins ({approx}99%) with known functions were expressed, whereas only approximately 80% of hypothetical proteins were detected in infected human cells. Quantitative MS/MS analyses indicated that highly expressed proteins in bothmore » bacteria included chaperones, enzymes involved in biosynthesis and metabolism, and outer membrane proteins, such as A. phagocytophilum P44 and E. chaffeensis P28/OMP-1. Among 113 A. phagocytophilum p44 paralogous genes, 110 of them were expressed and 88 of them were encoded by pseudogenes. In addition, bacterial infection of HL-60 cells up-regulated the expression of human proteins involved mostly in cytoskeleton components, vesicular trafficking, cell signaling, and energy metabolism, but down regulated some pattern recognition receptors involved in innate immunity. Our proteomics data represent a comprehensive analysis of A. phagocytophilum and E. chaffeensis proteomes, and provide a quantitative view of human host protein expression profiles regulated by bacterial infection. The availability of these proteomic data will provide new insights into biology and pathogenesis of these obligatory intracellular pathogens.« less

Proteomic analysis of enterotoxigenic Escherichia coli (ETEC) in neutral and alkaline conditions.

PubMed

Gonzales-Siles, Lucia; Karlsson, Roger; Kenny, Diarmuid; Karlsson, Anders; Sjöling, Åsa

2017-01-07

Enterotoxigenic Escherichia coli (ETEC) is a major cause of diarrhea in children and travelers to endemic areas. Secretion of the heat labile AB 5 toxin (LT) is induced by alkaline conditions. In this study, we determined the surface proteome of ETEC exposed to alkaline conditions (pH 9) as compared to neutral conditions (pH 7) using a LPI Hexalane FlowCell combined with quantitative proteomics. Relative quantitation with isobaric labeling (TMT) was used to compare peptide abundance and their corresponding proteins in multiple samples at MS/MS level. For protein identification and quantification samples were analyzed using either a 1D-LCMS or a 2D-LCMS approach. Strong up-regulation of the ATP synthase operon encoding F1Fo ATP synthase and down-regulation of proton pumping proteins NuoF, NuoG, Ndh and WrbA were detected among proteins involved in regulating the proton and electron transport under alkaline conditions. Reduced expression of proteins involved in osmotic stress was found at alkaline conditions while the Sec-dependent transport over the inner membrane and outer membrane protein proteins such as OmpA and the β-Barrel Assembly Machinery (BAM) complex were up-regulated. ETEC exposed to alkaline environments express a specific proteome profile characterized by up-regulation of membrane proteins and secretion of LT toxin. Alkaline microenvironments have been reported close to the intestinal epithelium and the alkaline proteome may hence represent a better view of ETEC during infection.

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

PubMed

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

2017-04-01

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

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

PubMed

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

2015-10-30

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

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

NASA Astrophysics Data System (ADS)

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

2017-04-01

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

Proteomics analyses for the global proteins in the brain tissues of different human prion diseases.

PubMed

Shi, Qi; Chen, Li-Na; Zhang, Bao-Yun; Xiao, Kang; Zhou, Wei; Chen, Cao; Zhang, Xiao-Mei; Tian, Chan; Gao, Chen; Wang, Jing; Han, Jun; Dong, Xiao-Ping

2015-04-01

Proteomics changes of brain tissues have been described in different neurodegenerative diseases including Alzheimer's disease and Parkinson's disease. However, the brain proteomics of human prion disease remains less understood. In the study, the proteomics patterns of cortex and cerebellum of brain tissues of sporadic Creutzfeldt-Jakob disease, fatal familial insomnia, and G114V genetic CJD were analyzed with isobaric tags for relative and absolute quantitation combined with multidimensional liquid chromatography and MS analysis, with the brains from three normal individuals as controls. Global protein profiling, significant pathway, and functional categories were analyzed. In total, 2287 proteins were identified with quantitative information both in cortex and cerebellum regions. Cerebellum tissues appeared to contain more up- and down-regulated proteins (727 proteins) than cortex regions (312 proteins) of Creutzfeldt-Jakob disease, fatal familial insomnia, and G114V genetic CJD. Viral myocarditis, Parkinson's disease, Alzheimer's disease, lysosome, oxidative phosphorylation, protein export, and drug metabolism-cytochrome P450 were the most commonly affected pathways of the three kinds of diseases. Almost coincident biological functions were identified in the brain tissues of the three diseases. In all, data here demonstrate that the brain tissues of Creutzfeldt-Jakob disease, fatal familial insomnia, and G114V genetic CJD have obvious proteomics changes at their terminal stages, which show the similarities not only among human prion diseases but also with other neurodegeneration diseases. This is the first study to provide a reference proteome map for human prion diseases and will be helpful for future studies focused on potential biomarkers for the diagnosis and therapy of human prion diseases. © 2015 by The American Society for Biochemistry and Molecular Biology, Inc.

Proteomics for understanding miRNA biology.

PubMed

Huang, Tai-Chung; Pinto, Sneha M; Pandey, Akhilesh

2013-02-01

MicroRNAs (miRNAs) are small noncoding RNAs that play important roles in posttranscriptional regulation of gene expression. Mature miRNAs associate with the RNA interference silencing complex to repress mRNA translation and/or degrade mRNA transcripts. Mass spectrometry-based proteomics has enabled identification of several core components of the canonical miRNA processing pathway and their posttranslational modifications which are pivotal in miRNA regulatory mechanisms. The use of quantitative proteomic strategies has also emerged as a key technique for experimental identification of miRNA targets by allowing direct determination of proteins whose levels are altered because of translational suppression. This review focuses on the role of proteomics and labeling strategies to understand miRNA biology. © 2012 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

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.

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.

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).

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

PubMed

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

2018-03-20

Jasmonate ZIM-domain (JAZ) proteins are key transcriptional repressors regulating various biological processes. Although many studies have studied JAZ proteins by genetic and biochemical analyses, little is known about JAZ7-associated global protein networks and how JAZ7 contributes to bacterial pathogen defense. In this study, we aim to fill this knowledge gap by conducting unbiased large-scale quantitative proteomics using tandem mass tags (TMT). We compared the proteomes of a JAZ7 knock-out line, a JAZ7 overexpression line, as well as the wild type Arabidopsis plants in the presence and absence of Pseudomonas syringae DC3000 infection. Both pairwise comparison and multi-factor analysis of variance reveal that differential proteins are enriched in biological processes such as primary and secondary metabolism, redox regulation, and response to stress. The differential regulation in these pathways may account for the alterations in plant size, redox homeostasis and accumulation of glucosinolates. In addition, possible interplay between genotype and environment is suggested as the abundance of seven proteins is influenced by the interaction of the two factors. Collectively, we demonstrate a role of JAZ7 in pathogen defense and provide a list of proteins that are uniquely responsive to genetic disruption, pathogen infection, or the interaction between genotypes and environmental factors. We report proteomic changes as a result of genetic perturbation of JAZ7, and the contribution of JAZ7 in plant immunity. Specifically, the similarity between the proteomes of a JAZ7 knockout mutant and the wild type plants confirmed the functional redundancy of JAZs. In contrast, JAZ7 overexpression plants were much different, and proteomic analysis of the JAZ7 overexpression plants under Pst DC3000 infection revealed that JAZ7 may regulate plant immunity via ROS modulation, energy balance and glucosinolate biosynthesis. Multiple variate analysis for this two-factor proteomics experiment suggests that protein abundance is determined by genotype, environment and the interaction between them. Copyright © 2018 Elsevier B.V. All rights reserved.

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

PubMed

Arntzen, Magnus Ø; Thiede, Bernd

2012-02-01

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

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

PubMed Central

Arntzen, Magnus Ø.; Thiede, Bernd

2012-01-01

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

Proteomic analysis of ligamentum flavum from patients with lumbar spinal stenosis.

PubMed

Kamita, Masahiro; Mori, Taiki; Sakai, Yoshihito; Ito, Sadayuki; Gomi, Masahiro; Miyamoto, Yuko; Harada, Atsushi; Niida, Shumpei; Yamada, Tesshi; Watanabe, Ken; Ono, Masaya

2015-05-01

Lumbar spinal stenosis (LSS) is a syndromic degenerative spinal disease and is characterized by spinal canal narrowing with subsequent neural compression causing gait disturbances. Although LSS is a major age-related musculoskeletal disease that causes large decreases in the daily living activities of the elderly, its molecular pathology has not been investigated using proteomics. Thus, we used several proteomic technologies to analyze the ligamentum flavum (LF) of individuals with LSS. Using comprehensive proteomics with strong cation exchange fractionation, we detected 1288 proteins in these LF samples. A GO analysis of the comprehensive proteome revealed that more than 30% of the identified proteins were extracellular. Next, we used 2D image converted analysis of LC/MS to compare LF obtained from individuals with LSS to that obtained from individuals with disc herniation (nondegenerative control). We detected 64 781 MS peaks and identified 1675 differentially expressed peptides derived from 286 proteins. We verified four differentially expressed proteins (fibronectin, serine protease HTRA1, tenascin, and asporin) by quantitative proteomics using SRM/MRM. The present proteomic study is the first to identify proteins from degenerated and hypertrophied LF in LSS, which will help in studying LSS. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Dynamic regulation of hepatic lipid droplet properties by diet.

PubMed

Crunk, Amanda E; Monks, Jenifer; Murakami, Aya; Jackman, Matthew; Maclean, Paul S; Ladinsky, Mark; Bales, Elise S; Cain, Shannon; Orlicky, David J; McManaman, James L

2013-01-01

Cytoplasmic lipid droplets (CLD) are organelle-like structures that function in neutral lipid storage, transport and metabolism through the actions of specific surface-associated proteins. Although diet and metabolism influence hepatic CLD levels, how they affect CLD protein composition is largely unknown. We used non-biased, shotgun, proteomics in combination with metabolic analysis, quantitative immunoblotting, electron microscopy and confocal imaging to define the effects of low- and high-fat diets on CLD properties in fasted-refed mice. We found that the hepatic CLD proteome is distinct from that of CLD from other mammalian tissues, containing enzymes from multiple metabolic pathways. The hepatic CLD proteome is also differentially affected by dietary fat content and hepatic metabolic status. High fat feeding markedly increased the CLD surface density of perilipin-2, a critical regulator of hepatic neutral lipid storage, whereas it reduced CLD levels of betaine-homocysteine S-methyltransferase, an enzyme regulator of homocysteine levels linked to fatty liver disease and hepatocellular carcinoma. Collectively our data demonstrate that the hepatic CLD proteome is enriched in metabolic enzymes, and that it is qualitatively and quantitatively regulated by diet and metabolism. These findings implicate CLD in the regulation of hepatic metabolic processes, and suggest that their properties undergo reorganization in response to hepatic metabolic demands.

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

PubMed Central

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

2016-01-01

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

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

PubMed Central

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

2014-01-01

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

Dynamic Regulation of Hepatic Lipid Droplet Properties by Diet

PubMed Central

Crunk, Amanda E.; Monks, Jenifer; Murakami, Aya; Jackman, Matthew; MacLean, Paul S.; Ladinsky, Mark; Bales, Elise S.; Cain, Shannon; Orlicky, David J.; McManaman, James L.

2013-01-01

Cytoplasmic lipid droplets (CLD) are organelle-like structures that function in neutral lipid storage, transport and metabolism through the actions of specific surface-associated proteins. Although diet and metabolism influence hepatic CLD levels, how they affect CLD protein composition is largely unknown. We used non-biased, shotgun, proteomics in combination with metabolic analysis, quantitative immunoblotting, electron microscopy and confocal imaging to define the effects of low- and high-fat diets on CLD properties in fasted-refed mice. We found that the hepatic CLD proteome is distinct from that of CLD from other mammalian tissues, containing enzymes from multiple metabolic pathways. The hepatic CLD proteome is also differentially affected by dietary fat content and hepatic metabolic status. High fat feeding markedly increased the CLD surface density of perilipin-2, a critical regulator of hepatic neutral lipid storage, whereas it reduced CLD levels of betaine-homocysteine S-methyltransferase, an enzyme regulator of homocysteine levels linked to fatty liver disease and hepatocellular carcinoma. Collectively our data demonstrate that the hepatic CLD proteome is enriched in metabolic enzymes, and that it is qualitatively and quantitatively regulated by diet and metabolism. These findings implicate CLD in the regulation of hepatic metabolic processes, and suggest that their properties undergo reorganization in response to hepatic metabolic demands. PMID:23874434

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.

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

PubMed

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

2011-06-01

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

Garlic (Allium sativum L.) fertility: transcriptome and proteome analyses provide insight into flower and pollen development

PubMed Central

Shemesh-Mayer, Einat; Ben-Michael, Tomer; Rotem, Neta; Rabinowitch, Haim D.; Doron-Faigenboim, Adi; Kosmala, Arkadiusz; Perlikowski, Dawid; Sherman, Amir; Kamenetsky, Rina

2015-01-01

Commercial cultivars of garlic, a popular condiment, are sterile, making genetic studies and breeding of this plant challenging. However, recent fertility restoration has enabled advanced physiological and genetic research and hybridization in this important crop. Morphophysiological studies, combined with transcriptome and proteome analyses and quantitative PCR validation, enabled the identification of genes and specific processes involved in gametogenesis in fertile and male-sterile garlic genotypes. Both genotypes exhibit normal meiosis at early stages of anther development, but in the male-sterile plants, tapetal hypertrophy after microspore release leads to pollen degeneration. Transcriptome analysis and global gene-expression profiling showed that >16,000 genes are differentially expressed in the fertile vs. male-sterile developing flowers. Proteome analysis and quantitative comparison of 2D-gel protein maps revealed 36 significantly different protein spots, 9 of which were present only in the male-sterile genotype. Bioinformatic and quantitative PCR validation of 10 candidate genes exhibited significant expression differences between male-sterile and fertile flowers. A comparison of morphophysiological and molecular traits of fertile and male-sterile garlic flowers suggests that respiratory restrictions and/or non-regulated programmed cell death of the tapetum can lead to energy deficiency and consequent pollen abortion. Potential molecular markers for male fertility and sterility in garlic are proposed. PMID:25972879

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

PubMed

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

2016-08-11

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

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

PubMed

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

2017-04-01

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

Serum Proteome Analysis for Profiling Predictive Protein Markers Associated with the Severity of Skin Lesions Induced by Ionizing Radiation.

PubMed

Chaze, Thibault; Hornez, Louis; Chambon, Christophe; Haddad, Iman; Vinh, Joelle; Peyrat, Jean-Philippe; Benderitter, Marc; Guipaud, Olivier

2013-07-10

The finding of new diagnostic and prognostic markers of local radiation injury, and particularly of the cutaneous radiation syndrome, is crucial for its medical management, in the case of both accidental exposure and radiotherapy side effects. Especially, a fast high-throughput method is still needed for triage of people accidentally exposed to ionizing radiation. In this study, we investigated the impact of localized irradiation of the skin on the early alteration of the serum proteome of mice in an effort to discover markers associated with the exposure and severity of impending damage. Using two different large-scale quantitative proteomic approaches, 2D-DIGE-MS and SELDI-TOF-MS, we performed global analyses of serum proteins collected in the clinical latency phase (days 3 and 7) from non-irradiated and locally irradiated mice exposed to high doses of 20, 40 and 80 Gy which will develop respectively erythema, moist desquamation and necrosis. Unsupervised and supervised multivariate statistical analyses (principal component analysis, partial-least square discriminant analysis and Random Forest analysis) using 2D-DIGE quantitative protein data allowed us to discriminate early between non-irradiated and irradiated animals, and between uninjured/slightly injured animals and animals that will develop severe lesions. On the other hand, despite a high number of animal replicates, PLS-DA and Random Forest analyses of SELDI-TOF-MS data failed to reveal sets of MS peaks able to discriminate between the different groups of animals. Our results show that, unlike SELDI-TOF-MS, the 2D-DIGE approach remains a powerful and promising method for the discovery of sets of proteins that could be used for the development of clinical tests for triage and the prognosis of the severity of radiation-induced skin lesions. We propose a list of 15 proteins which constitutes a set of candidate proteins for triage and prognosis of skin lesion outcomes.

Serum Proteome Analysis for Profiling Predictive Protein Markers Associated with the Severity of Skin Lesions Induced by Ionizing Radiation

PubMed Central

Chaze, Thibault; Hornez, Louis; Chambon, Christophe; Haddad, Iman; Vinh, Joelle; Peyrat, Jean-Philippe; Benderitter, Marc; Guipaud, Olivier

2013-01-01

The finding of new diagnostic and prognostic markers of local radiation injury, and particularly of the cutaneous radiation syndrome, is crucial for its medical management, in the case of both accidental exposure and radiotherapy side effects. Especially, a fast high-throughput method is still needed for triage of people accidentally exposed to ionizing radiation. In this study, we investigated the impact of localized irradiation of the skin on the early alteration of the serum proteome of mice in an effort to discover markers associated with the exposure and severity of impending damage. Using two different large-scale quantitative proteomic approaches, 2D-DIGE-MS and SELDI-TOF-MS, we performed global analyses of serum proteins collected in the clinical latency phase (days 3 and 7) from non-irradiated and locally irradiated mice exposed to high doses of 20, 40 and 80 Gy which will develop respectively erythema, moist desquamation and necrosis. Unsupervised and supervised multivariate statistical analyses (principal component analysis, partial-least square discriminant analysis and Random Forest analysis) using 2D-DIGE quantitative protein data allowed us to discriminate early between non-irradiated and irradiated animals, and between uninjured/slightly injured animals and animals that will develop severe lesions. On the other hand, despite a high number of animal replicates, PLS-DA and Random Forest analyses of SELDI-TOF-MS data failed to reveal sets of MS peaks able to discriminate between the different groups of animals. Our results show that, unlike SELDI-TOF-MS, the 2D-DIGE approach remains a powerful and promising method for the discovery of sets of proteins that could be used for the development of clinical tests for triage and the prognosis of the severity of radiation-induced skin lesions. We propose a list of 15 proteins which constitutes a set of candidate proteins for triage and prognosis of skin lesion outcomes. PMID:28250398

Metabolic Labeling and Membrane Fractionation for Comparative Proteomic Analysis of Arabidopsis thaliana Suspension Cell Cultures

PubMed Central

Szymanski, Witold G.; Kierszniowska, Sylwia; Schulze, Waltraud X.

2013-01-01

Plasma membrane microdomains are features based on the physical properties of the lipid and sterol environment and have particular roles in signaling processes. Extracting sterol-enriched membrane microdomains from plant cells for proteomic analysis is a difficult task mainly due to multiple preparation steps and sources for contaminations from other cellular compartments. The plasma membrane constitutes only about 5-20% of all the membranes in a plant cell, and therefore isolation of highly purified plasma membrane fraction is challenging. A frequently used method involves aqueous two-phase partitioning in polyethylene glycol and dextran, which yields plasma membrane vesicles with a purity of 95% 1. Sterol-rich membrane microdomains within the plasma membrane are insoluble upon treatment with cold nonionic detergents at alkaline pH. This detergent-resistant membrane fraction can be separated from the bulk plasma membrane by ultracentrifugation in a sucrose gradient 2. Subsequently, proteins can be extracted from the low density band of the sucrose gradient by methanol/chloroform precipitation. Extracted protein will then be trypsin digested, desalted and finally analyzed by LC-MS/MS. Our extraction protocol for sterol-rich microdomains is optimized for the preparation of clean detergent-resistant membrane fractions from Arabidopsis thaliana cell cultures. We use full metabolic labeling of Arabidopsis thaliana suspension cell cultures with K15NO3 as the only nitrogen source for quantitative comparative proteomic studies following biological treatment of interest 3. By mixing equal ratios of labeled and unlabeled cell cultures for joint protein extraction the influence of preparation steps on final quantitative result is kept at a minimum. Also loss of material during extraction will affect both control and treatment samples in the same way, and therefore the ratio of light and heave peptide will remain constant. In the proposed method either labeled or unlabeled cell culture undergoes a biological treatment, while the other serves as control 4. PMID:24121251

A Systems Level Analysis Reveals Transcriptomic and Proteomic Complexity in Ixodes Ricinus Midgut and Salivary Glands During Early Attachment and Feeding*

PubMed Central

Schwarz, Alexandra; Tenzer, Stefan; Hackenberg, Michael; Erhart, Jan; Gerhold-Ay, Aslihan; Mazur, Johanna; Kuharev, Jörg; Ribeiro, José M. C.; Kotsyfakis, Michail

2014-01-01

Although pathogens are usually transmitted within the first 24–48 h of attachment of the castor bean tick Ixodes ricinus, little is known about the tick's biological responses at these earliest phases of attachment. Tick midgut and salivary glands are the main tissues involved in tick blood feeding and pathogen transmission but the limited genomic information for I. ricinus delays the application of high-throughput methods to study their physiology. We took advantage of the latest advances in the fields of Next Generation RNA-Sequencing and Label-free Quantitative Proteomics to deliver an unprecedented, quantitative description of the gene expression dynamics in the midgut and salivary glands of this disease vector upon attachment to the vertebrate host. A total of 373 of 1510 identified proteins had higher expression in the salivary glands, but only 110 had correspondingly high transcript levels in the same tissue. Furthermore, there was midgut-specific expression of 217 genes at both the transcriptome and proteome level. Tissue-dependent transcript, but not protein, accumulation was revealed for 552 of 885 genes. Moreover, we discovered the enrichment of tick salivary glands in proteins involved in gene transcription and translation, which agrees with the secretory role of this tissue; this finding also agrees with our finding of lower tick t-RNA representation in the salivary glands when compared with the midgut. The midgut, in turn, is enriched in metabolic components and proteins that support its mechanical integrity in order to accommodate and metabolize the ingested blood. Beyond understanding the physiological events that support hematophagy by arthropod ectoparasites, we discovered more than 1500 proteins located at the interface between ticks, the vertebrate host, and the tick-borne pathogens. Thus, our work significantly improves the knowledge of the genetics underlying the transmission lifecycle of this tick species, which is an essential step for developing alternative methods to better control tick-borne diseases. PMID:25048707

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.

Proteomics in food: Quality, safety, microbes, and allergens.

PubMed

Piras, Cristian; Roncada, Paola; Rodrigues, Pedro M; Bonizzi, Luigi; Soggiu, Alessio

2016-03-01

Food safety and quality and their associated risks pose a major concern worldwide regarding not only the relative economical losses but also the potential danger to consumer's health. Customer's confidence in the integrity of the food supply could be hampered by inappropriate food safety measures. A lack of measures and reliable assays to evaluate and maintain a good control of food characteristics may affect the food industry economy and shatter consumer confidence. It is imperative to create and to establish fast and reliable analytical methods that allow a good and rapid analysis of food products during the whole food chain. Proteomics can represent a powerful tool to address this issue, due to its proven excellent quantitative and qualitative drawbacks in protein analysis. This review illustrates the applications of proteomics in the past few years in food science focusing on food of animal origin with some brief hints on other types. Aim of this review is to highlight the importance of this science as a valuable tool to assess food quality and safety. Emphasis is also posed in food processing, allergies, and possible contaminants like bacteria, fungi, and other pathogens. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

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

PubMed

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

2018-01-01

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

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

PubMed

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

2018-04-06

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

Quantitative proteomic analysis reveals a simple strategy of global resource allocation in bacteria

PubMed Central

Hui, Sheng; Silverman, Josh M; Chen, Stephen S; Erickson, David W; Basan, Markus; Wang, Jilong; Hwa, Terence; Williamson, James R

2015-01-01

A central aim of cell biology was to understand the strategy of gene expression in response to the environment. Here, we study gene expression response to metabolic challenges in exponentially growing Escherichia coli using mass spectrometry. Despite enormous complexity in the details of the underlying regulatory network, we find that the proteome partitions into several coarse-grained sectors, with each sector's total mass abundance exhibiting positive or negative linear relations with the growth rate. The growth rate-dependent components of the proteome fractions comprise about half of the proteome by mass, and their mutual dependencies can be characterized by a simple flux model involving only two effective parameters. The success and apparent generality of this model arises from tight coordination between proteome partition and metabolism, suggesting a principle for resource allocation in proteome economy of the cell. This strategy of global gene regulation should serve as a basis for future studies on gene expression and constructing synthetic biological circuits. Coarse graining may be an effective approach to derive predictive phenomenological models for other ‘omics’ studies. PMID:25678603

Proteomic Analysis of Lipid Raft-Like Detergent-Resistant Membranes of Lens Fiber Cells

PubMed Central

Wang, Zhen; Schey, Kevin L.

2015-01-01

Purpose Plasma membranes of lens fiber cells have high levels of long-chain saturated fatty acids, cholesterol, and sphingolipids—key components of lipid rafts. Thus, lipid rafts are expected to constitute a significant portion of fiber cell membranes and play important roles in lens biology. The purpose of this study was to characterize the lens lipid raft proteome. Methods Quantitative proteomics, both label-free and iTRAQ methods, were used to characterize lens fiber cell lipid raft proteins. Detergent-resistant, lipid raft membrane (DRM) fractions were isolated by sucrose gradient centrifugation. To confirm protein localization to lipid rafts, protein sensitivity to cholesterol removal by methyl-β-cyclodextrin was quantified by iTRAQ analysis. Results A total of 506 proteins were identified in raft-like detergent-resistant membranes. Proteins identified support important functions of raft domains in fiber cells, including trafficking, signal transduction, and cytoskeletal organization. In cholesterol-sensitivity studies, 200 proteins were quantified and 71 proteins were strongly affected by cholesterol removal. Lipid raft markers flotillin-1 and flotillin-2 and a significant fraction of AQP0, MP20, and AQP5 were found in the DRM fraction and were highly sensitive to cholesterol removal. Connexins 46 and 50 were more abundant in nonraft fractions, but a small fraction of each was found in the DRM fraction and was strongly affected by cholesterol removal. Quantification of modified AQP0 confirmed that fatty acylation targeted this protein to membrane raft domains. Conclusions These data represent the first comprehensive profile of the lipid raft proteome of lens fiber cells and provide information on membrane protein organization in these cells. PMID:26747763

Quantitative Shotgun Proteomics Using a Uniform 15N-Labeled Standard to Monitor Proteome Dynamics in Time Course Experiments Reveals New Insights into the Heat Stress Response of Chlamydomonas reinhardtii*

PubMed Central

Mühlhaus, Timo; Weiss, Julia; Hemme, Dorothea; Sommer, Frederik; Schroda, Michael

2011-01-01

Crop-plant-yield safety is jeopardized by temperature stress caused by the global climate change. To take countermeasures by breeding and/or transgenic approaches it is essential to understand the mechanisms underlying plant acclimation to heat stress. To this end proteomics approaches are most promising, as acclimation is largely mediated by proteins. Accordingly, several proteomics studies, mainly based on two-dimensional gel-tandem MS approaches, were conducted in the past. However, results often were inconsistent, presumably attributable to artifacts inherent to the display of complex proteomes via two-dimensional-gels. We describe here a new approach to monitor proteome dynamics in time course experiments. This approach involves full 15N metabolic labeling and mass spectrometry based quantitative shotgun proteomics using a uniform 15N standard over all time points. It comprises a software framework, IOMIQS, that features batch job mediated automated peptide identification by four parallelized search engines, peptide quantification and data assembly for the processing of large numbers of samples. We have applied this approach to monitor proteome dynamics in a heat stress time course using the unicellular green alga Chlamydomonas reinhardtii as model system. We were able to identify 3433 Chlamydomonas proteins, of which 1116 were quantified in at least three of five time points of the time course. Statistical analyses revealed that levels of 38 proteins significantly increased, whereas levels of 206 proteins significantly decreased during heat stress. The increasing proteins comprise 25 (co-)chaperones and 13 proteins involved in chromatin remodeling, signal transduction, apoptosis, photosynthetic light reactions, and yet unknown functions. Proteins decreasing during heat stress were significantly enriched in functional categories that mediate carbon flux from CO2 and external acetate into protein biosynthesis, which also correlated with a rapid, but fully reversible cell cycle arrest after onset of stress. Our approach opens up new perspectives for plant systems biology and provides novel insights into plant stress acclimation. PMID:21610104

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.

Statistical Model to Analyze Quantitative Proteomics Data Obtained by 18O/16O Labeling and Linear Ion Trap Mass Spectrometry

PubMed Central

Jorge, Inmaculada; Navarro, Pedro; Martínez-Acedo, Pablo; Núñez, Estefanía; Serrano, Horacio; Alfranca, Arántzazu; Redondo, Juan Miguel; Vázquez, Jesús

2009-01-01

Statistical models for the analysis of protein expression changes by stable isotope labeling are still poorly developed, particularly for data obtained by 16O/18O labeling. Besides large scale test experiments to validate the null hypothesis are lacking. Although the study of mechanisms underlying biological actions promoted by vascular endothelial growth factor (VEGF) on endothelial cells is of considerable interest, quantitative proteomics studies on this subject are scarce and have been performed after exposing cells to the factor for long periods of time. In this work we present the largest quantitative proteomics study to date on the short term effects of VEGF on human umbilical vein endothelial cells by 18O/16O labeling. Current statistical models based on normality and variance homogeneity were found unsuitable to describe the null hypothesis in a large scale test experiment performed on these cells, producing false expression changes. A random effects model was developed including four different sources of variance at the spectrum-fitting, scan, peptide, and protein levels. With the new model the number of outliers at scan and peptide levels was negligible in three large scale experiments, and only one false protein expression change was observed in the test experiment among more than 1000 proteins. The new model allowed the detection of significant protein expression changes upon VEGF stimulation for 4 and 8 h. The consistency of the changes observed at 4 h was confirmed by a replica at a smaller scale and further validated by Western blot analysis of some proteins. Most of the observed changes have not been described previously and are consistent with a pattern of protein expression that dynamically changes over time following the evolution of the angiogenic response. With this statistical model the 18O labeling approach emerges as a very promising and robust alternative to perform quantitative proteomics studies at a depth of several thousand proteins. PMID:19181660

A Straightforward and Highly Efficient Precipitation/On-pellet Digestion Procedure Coupled to a Long Gradient Nano-LC Separation and Orbitrap Mass Spectrometry for Label-free Expression Profiling of the Swine Heart Mitochondrial Proteome

PubMed Central

Duan, Xiaotao; Young, Rebecca; Straubinger, Robert M.; Page, Brian J.; Cao, Jin; Wang, Hao; Yu, Haoying; Canty, John M.; Qu, Jun

2009-01-01

For label-free expression profiling of tissue proteomes, efficient protein extraction, thorough and quantitative sample cleanup and digestion procedures, as well as sufficient and reproducible chromatographic separation, are highly desirable but remain challenging. However, optimal methodology has remained elusive, especially for proteomes that are rich in membrane proteins, such as the mitochondria. Here we describe a straightforward and reproducible sample preparation procedure, coupled with a highly selective and sensitive nano-LC/Orbitrap analysis, which enables reliable and comprehensive expression profiling of tissue mitochondria. The mitochondrial proteome of swine heart was selected as a test system. Efficient protein extraction was accomplished using a strong buffer containing both ionic and non-ionic detergents. Overnight precipitation was used for cleanup of the extract, and the sample was subjected to an optimized 2-step, on-pellet digestion approach. In the first step, the protein pellet was dissolved via a 4 h tryptic digestion under vigorous agitation, which nano-LC/LTQ/ETD showed to produce large and incompletely cleaved tryptic peptides. The mixture was then reduced, alkylated, and digested into its full complement of tryptic peptides with additional trypsin. This solvent precipitation/on-pellet digestion procedure achieved significantly higher and more reproducible peptide recovery of the mitochondrial preparation, than observed using a prevalent alternative procedure for label-free expression profiling, SDS-PAGE/in-gel digestion (87% vs. 54%). Furthermore, uneven peptide losses were lower than observed with SDS-PAGE/in-gel digestion. The resulting peptides were sufficiently resolved by a 5 h gradient using a nano-LC configuration that features a low-void-volume, high chromatographic reproducibility, and an LTQ/Orbitrap analyzer for protein identification and quantification. The developed method was employed for label-free comparison of the mitochondrial proteomes of myocardium from healthy animals vs. those with hibernating myocardium. Each experimental group consisted of a relatively large number of animals (n=10), and samples were analyzed in random order to minimize quantitative false-positives. Using this approach, 904 proteins were identified and quantified with high confidence, and those mitochondrial proteins that were altered significantly between groups were compared with the results of a parallel 2D-DIGE analysis. The sample preparation and analytical strategy developed here represents an advancement that can be adapted to analyze other tissue proteomes. PMID:19290621

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.

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.

Recent advances in proteomics of cereals.

PubMed

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

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

Detection and quantification of proteins and cells by use of elemental mass spectrometry: progress and challenges.

PubMed

Yan, Xiaowen; Yang, Limin; Wang, Qiuquan

2013-07-01

Much progress has been made in identification of the proteins in proteomes, and quantification of these proteins has attracted much interest. In addition to popular tandem mass spectrometric methods based on soft ionization, inductively coupled plasma mass spectrometry (ICPMS), a typical example of mass spectrometry based on hard ionization, usually used for analysis of elements, has unique advantages in absolute quantification of proteins by determination of an element with a definite stoichiometry in a protein or attached to the protein. In this Trends article, we briefly describe state-of-the-art ICPMS-based methods for quantification of proteins, emphasizing protein-labeling and element-tagging strategies developed on the basis of chemically selective reactions and/or biospecific interactions. Recent progress from protein to cell quantification by use of ICPMS is also discussed, and the possibilities and challenges of ICPMS-based protein quantification for universal, selective, or targeted quantification of proteins and cells in a biological sample are also discussed critically. We believe ICPMS-based protein quantification will become ever more important in targeted quantitative proteomics and bioanalysis in the near future.

An MRM-based workflow for quantifying cardiac mitochondrial protein phosphorylation in murine and human tissue.

PubMed

Lam, Maggie P Y; Scruggs, Sarah B; Kim, Tae-Young; Zong, Chenggong; Lau, Edward; Wang, Ding; Ryan, Christopher M; Faull, Kym F; Ping, Peipei

2012-08-03

The regulation of mitochondrial function is essential for cardiomyocyte adaptation to cellular stress. While it has long been understood that phosphorylation regulates flux through metabolic pathways, novel phosphorylation sites are continually being discovered in all functionally distinct areas of the mitochondrial proteome. Extracting biologically meaningful information from these phosphorylation sites requires an adaptable, sensitive, specific and robust method for their quantification. Here we report a multiple reaction monitoring-based mass spectrometric workflow for quantifying site-specific phosphorylation of mitochondrial proteins. Specifically, chromatographic and mass spectrometric conditions for 68 transitions derived from 23 murine and human phosphopeptides, and their corresponding unmodified peptides, were optimized. These methods enabled the quantification of endogenous phosphopeptides from the outer mitochondrial membrane protein VDAC, and the inner membrane proteins ANT and ETC complexes I, III and V. The development of this quantitative workflow is a pivotal step for advancing our knowledge and understanding of the regulatory effects of mitochondrial protein phosphorylation in cardiac physiology and pathophysiology. This article is part of a Special Issue entitled: Translational Proteomics. Copyright © 2012 Elsevier B.V. All rights reserved.

Development of Best practices document for Peptide Standards | Office of Cancer Clinical Proteomics Research

Cancer.gov

The Assay Development Working Group (ADWG) of the CPTAC Program is currently drafting a document to propose best practices for generation, quantification, storage, and handling of peptide standards used for mass spectrometry-based assays, as well as interpretation of quantitative proteomic data based on peptide standards. The ADWG is seeking input from commercial entities that provide peptide standards for mass spectrometry-based assays or that perform amino acid analysis.

A New Algorithm Using Cross-Assignment for Label-Free Quantitation with LC/LTQ-FT MS

PubMed Central

Andreev, Victor P.; Li, Lingyun; Cao, Lei; Gu, Ye; Rejtar, Tomas; Wu, Shiaw-Lin; Karger, Barry L.

2008-01-01

A new algorithm is described for label-free quantitation of relative protein abundances across multiple complex proteomic samples. Q-MEND is based on the denoising and peak picking algorithm, MEND, previously developed in our laboratory. Q-MEND takes advantage of the high resolution and mass accuracy of the hybrid LTQFT MS mass spectrometer (or other high resolution mass spectrometers, such as a Q-TOF MS). The strategy, termed “cross-assignment”, is introduced to increase substantially the number of quantitated proteins. In this approach, all MS/MS identifications for the set of analyzed samples are combined into a master ID list, and then each LC/MS run is searched for the features that can be assigned to a specific identification from that master list. The reliability of quantitation is enhanced by quantitating separately all peptide charge states, along with a scoring procedure to filter out less reliable peptide abundance measurements. The effectiveness of Q-MEND is illustrated in the relative quantitative analysis of E.coli samples spiked with known amounts of non-E.coli protein digests. A mean quantitation accuracy of 7% and mean precision of 15% is demonstrated. Q-MEND can perform relative quantitation of a set of LC/MS datasets without manual intervention and can generate files compatible with the Guidelines for Proteomic Data Publication. PMID:17441747

A new algorithm using cross-assignment for label-free quantitation with LC-LTQ-FT MS.

PubMed

Andreev, Victor P; Li, Lingyun; Cao, Lei; Gu, Ye; Rejtar, Tomas; Wu, Shiaw-Lin; Karger, Barry L

2007-06-01

A new algorithm is described for label-free quantitation of relative protein abundances across multiple complex proteomic samples. Q-MEND is based on the denoising and peak picking algorithm, MEND, previously developed in our laboratory. Q-MEND takes advantage of the high resolution and mass accuracy of the hybrid LTQ-FT MS mass spectrometer (or other high-resolution mass spectrometers, such as a Q-TOF MS). The strategy, termed "cross-assignment", is introduced to increase substantially the number of quantitated proteins. In this approach, all MS/MS identifications for the set of analyzed samples are combined into a master ID list, and then each LC-MS run is searched for the features that can be assigned to a specific identification from that master list. The reliability of quantitation is enhanced by quantitating separately all peptide charge states, along with a scoring procedure to filter out less reliable peptide abundance measurements. The effectiveness of Q-MEND is illustrated in the relative quantitative analysis of Escherichia coli samples spiked with known amounts of non-E. coli protein digests. A mean quantitation accuracy of 7% and mean precision of 15% is demonstrated. Q-MEND can perform relative quantitation of a set of LC-MS data sets without manual intervention and can generate files compatible with the Guidelines for Proteomic Data Publication.

Changes over lactation in breast milk serum proteins involved in the maturation of immune and digestive system of the infant.

PubMed

Zhang, Lina; de Waard, Marita; Verheijen, Hester; Boeren, Sjef; Hageman, Jos A; van Hooijdonk, Toon; Vervoort, Jacques; van Goudoever, Johannes B; Hettinga, Kasper

2016-09-16

To objective of this study was to better understand the biological functions of breast milk proteins in relation to the growth and development of infants over the first six months of life. Breast milk samples from four individual women collected at seven time points in the first six months after delivery were analyzed by filter aided sample preparation and dimethyl labeling combined with liquid chromatography tandem mass spectrometry. A total of 247 and 200 milk serum proteins were identified and quantified, respectively. The milk serum proteome showed a high similarity (80% overlap) on the qualitative level between women and over lactation. The quantitative changes in milk serum proteins were mainly caused by three groups of proteins, enzymes, and transport and immunity proteins. Of these 21 significantly changed proteins, 30% were transport proteins, such as serum albumin and fatty acid binding protein, which are both involved in transporting nutrients to the infant. The decrease of the enzyme bile salt-activated lipase as well as the immunity proteins immunoglobulins and lactoferrin coincide with the gradual maturation of the digestive and immune system of infants. The human milk serum proteome didn't differ qualitatively but it did quantitatively, both between mothers and as lactation advanced. The changes of the breast milk serum proteome over lactation corresponded with the development of the digestive and immune system of infants. Breast milk proteins provide nutrition, but also contribute to healthy development of infants. Despite the previously reported large number of identified breast milk proteins and their changes over lactation, less is known on the changes of these proteins in individual mothers. This study is the first to determine the qualitative and quantitative changes of milk proteome over lactation between individual mothers. The results indicate that the differences in the milk proteome between individual mothers are more related to the quantitative level than qualitative level. The correlation between the changes of milk proteins and the gradual maturation of the gastrointestinal tract and immune system in infants, contributes to a better understanding of the biological functions of human milk proteins for the growth and development of infants. Copyright © 2016 Elsevier B.V. All rights reserved.

Global combined precursor isotopic labeling and isobaric tagging (cPILOT) approach with selective MS(3) acquisition.

PubMed

Evans, Adam R; Robinson, Renã A S

2013-11-01

Recently, we reported a novel proteomics quantitation scheme termed "combined precursor isotopic labeling and isobaric tagging (cPILOT)" that allows for the identification and quantitation of nitrated peptides in as many as 12-16 samples in a single experiment. cPILOT offers enhanced multiplexing and posttranslational modification specificity, however excludes global quantitation for all peptides present in a mixture and underestimates reporter ion ratios similar to other isobaric tagging methods due to precursor co-isolation. Here, we present a novel chemical workflow for cPILOT that can be used for global tagging of all peptides in a mixture. Specifically, through low pH precursor dimethylation of tryptic or LysC peptides followed by high pH tandem mass tags, the same reporter ion can be used twice in a single experiment. Also, to improve triple-stage mass spectrometry (MS(3) ) data acquisition, a selective MS(3) method that focuses on product selection of the y1 fragment of lysine-terminated peptides is incorporated into the workflow. This novel cPILOT workflow has potential for global peptide quantitation that could lead to enhanced sample multiplexing and increase the number of quantifiable spectra obtained from MS(3) acquisition methods. © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

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

DOE PAGES

Sonnett, Matthew; Yeung, Eyan; Wuhr, Martin

2018-03-09

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

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

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

Sonnett, Matthew; Yeung, Eyan; Wuhr, Martin

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

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.

Mastitomics, the integrated omics of bovine milk in an experimental model of Streptococcus uberis mastitis: 2. Label-free relative quantitative proteomics† †Electronic supplementary information (ESI) available. See DOI: 10.1039/c6mb00290k Click here for additional data file.

PubMed Central

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

2016-01-01

Mastitis, inflammation of the mammary gland, is the most common and costly disease of dairy cattle in the western world. It is primarily caused by bacteria, with Streptococcus uberis as one of the most prevalent causative agents. To characterize the proteome during Streptococcus uberis mastitis, an experimentally induced model of intramammary infection was used. Milk whey samples obtained from 6 cows at 6 time points were processed using label-free relative quantitative proteomics. This proteomic analysis complements clinical, bacteriological and immunological studies as well as peptidomic and metabolomic analysis of the same challenge model. A total of 2552 non-redundant bovine peptides were identified, and from these, 570 bovine proteins were quantified. Hierarchical cluster analysis and principal component analysis showed clear clustering of results by stage of infection, with similarities between pre-infection and resolution stages (0 and 312 h post challenge), early infection stages (36 and 42 h post challenge) and late infection stages (57 and 81 h post challenge). Ingenuity pathway analysis identified upregulation of acute phase protein pathways over the course of infection, with dominance of different acute phase proteins at different time points based on differential expression analysis. Antimicrobial peptides, notably cathelicidins and peptidoglycan recognition protein, were upregulated at all time points post challenge and peaked at 57 h, which coincided with 10 000-fold decrease in average bacterial counts. The integration of clinical, bacteriological, immunological and quantitative proteomics and other-omic data provides a more detailed systems level view of the host response to mastitis than has been achieved previously. PMID:27412694

SWATH™- and iTRAQ-based quantitative proteomic analyses reveal an overexpression and biological relevance of CD109 in advanced NSCLC.

PubMed

Zhang, Fanglin; Lin, Hechun; Gu, Aiqin; Li, Jing; Liu, Lei; Yu, Tao; Cui, Yongqi; Deng, Wei; Yan, Mingxia; Li, Jinjun; Yao, Ming

2014-05-06

To identify cancer-related proteins, we used isobaric tags in a relative and absolute quantitation (iTRAQ) proteomic approach and SWATH™ quantification approach to analyze the secretome of an isogenic pair of highly metastatic and low metastatic non-small-cell lung cancer (NSCLC) cell lines. In addition, we compared two groups of pooled serum samples (12 early-stage and 12 late-stage patients) to mine data for candidates screened by iTRAQ-labeled proteomic analysis. A total of 110 proteins and 71 proteins were observed to be significantly differentially expressed in the cell line secretome and NSCLC sera, respectively. Among these proteins, CD109 was found to be highly expressed in both the highly metastatic cell line secretome and the group of late-stage patients. A sandwich ELISA assay also demonstrated an elevation of serum CD109 levels in individual NSCLC patients (n=30) compared with healthy subjects (n=19). Furthermore, CD109 displayed higher expression in lung cancer tissues compared with their matched noncancerous lung tissues (n=72). In addition, the knockdown of CD109 influenced several NSCLC cell bio-functions, for instance, depressing cell growth, affecting cell cycle phases. These phenomena suggest that CD109 plays a critical role in NSCLC progression. We simultaneously applied two quantitative proteomic approaches-iTRAQ-labeling and SWATH™-to analyze the secretome of metastatic cell lines, in order to explore the cancer-associated proteins in conditioned media. In this study, our results indicate that CD109 plays a critical role in non-small-cell lung cancer (NSCLC) progression, and is overexpressed in advanced NSCLC. Copyright © 2014 Elsevier B.V. All rights reserved.

Transcriptomic and Quantitative Proteomic Analyses Provide Insights Into the Phagocytic Killing of Hemocytes in the Oyster Crassostrea gigas

PubMed Central

Jiang, Shuai; Qiu, Limei; Wang, Lingling; Jia, Zhihao; Lv, Zhao; Wang, Mengqiang; Liu, Conghui; Xu, Jiachao; Song, Linsheng

2018-01-01

As invertebrates lack an adaptive immune system, they depend to a large extent on their innate immune system to recognize and clear invading pathogens. Although phagocytes play pivotal roles in invertebrate innate immunity, the molecular mechanisms underlying this killing remain unclear. Cells of this type from the Pacific oyster Crassostrea gigas were classified efficiently in this study via fluorescence-activated cell sorting (FACS) based on their phagocytosis of FITC-labeled latex beads. Transcriptomic and quantitative proteomic analyses revealed a series of differentially expressed genes (DEGs) and proteins present in phagocytes; of the 352 significantly high expressed proteins identified here within the phagocyte proteome, 262 corresponding genes were similarly high expressed in the transcriptome, while 140 of 205 significantly low expressed proteins within the proteome were transcriptionally low expressed. A pathway crosstalk network analysis of these significantly high expressed proteins revealed that phagocytes were highly activated in a number of antimicrobial-related biological processes, including oxidation–reduction and lysosomal proteolysis processes. A number of DEGs, including oxidase, lysosomal protease, and immune receptors, were also validated in this study using quantitative PCR, while seven lysosomal cysteine proteases, referred to as cathepsin Ls, were significantly high expressed in phagocytes. Results show that the expression level of cathepsin L protein in phagocytes [mean fluorescence intensity (MFI): 327 ± 51] was significantly higher (p < 0.01) than that in non-phagocytic hemocytes (MFI: 83 ± 26), while the cathepsin L protein was colocalized with the phagocytosed Vibrio splendidus in oyster hemocytes during this process. The results of this study collectively suggest that oyster phagocytes possess both potent oxidative killing and microbial disintegration capacities; these findings provide important insights into hemocyte phagocytic killing as a component of C. gigas innate immunity. PMID:29942306

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.

[Techniques for rapid production of monoclonal antibodies for use with antibody technology].

PubMed

Kamada, Haruhiko

2012-01-01

A monoclonal antibody (Mab), due to its specific binding ability to a target protein, can potentially be one of the most useful tools for the functional analysis of proteins in recent proteomics-based research. However, the production of Mab is a very time-consuming and laborious process (i.e., preparation of recombinant antigens, immunization of animals, preparation of hybridomas), making it the rate-limiting step in using Mabs in high-throughput proteomics research, which heavily relies on comprehensive and rapid methods. Therefore, there is a great demand for new methods to efficiently generate Mabs against a group of proteins identified by proteome analysis. Here, we describe a useful method called "Antibody proteomic technique" for the rapid generations of Mabs to pharmaceutical target, which were identified by proteomic analyses of disease samples (ex. tumor tissue, etc.). We also introduce another method to find profitable targets on vasculature, which is called "Vascular proteomic technique". Our results suggest that this method for the rapid generation of Mabs to proteins may be very useful in proteomics-based research as well as in clinical applications.

The selected reaction monitoring/multiple reaction monitoring-based mass spectrometry approach for the accurate quantitation of proteins: clinical applications in the cardiovascular diseases.

PubMed

Gianazza, Erica; Tremoli, Elena; Banfi, Cristina

2014-12-01

Selected reaction monitoring, also known as multiple reaction monitoring, is a powerful targeted mass spectrometry approach for a confident quantitation of proteins/peptides in complex biological samples. In recent years, its optimization and application have become pivotal and of great interest in clinical research to derive useful outcomes for patient care. Thus, selected reaction monitoring/multiple reaction monitoring is now used as a highly sensitive and selective method for the evaluation of protein abundances and biomarker verification with potential applications in medical screening. This review describes technical aspects for the development of a robust multiplex assay and discussing its recent applications in cardiovascular proteomics: verification of promising disease candidates to select only the highest quality peptides/proteins for a preclinical validation, as well as quantitation of protein isoforms and post-translational modifications.

Attomole quantitation of protein separations with accelerator mass spectrometry

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

Vogel, J S; Grant, P G; Buccholz, B A

2000-12-15

Quantification of specific proteins depends on separation by chromatography or electrophoresis followed by chemical detection schemes such as staining and fluorophore adhesion. Chemical exchange of short-lived isotopes, particularly sulfur, is also prevalent despite the inconveniences of counting radioactivity. Physical methods based on isotopic and elemental analyses offer highly sensitive protein quantitation that has linear response over wide dynamic ranges and is independent of protein conformation. Accelerator mass spectrometry quantifies long-lived isotopes such as 14C to sub-attomole sensitivity. We quantified protein interactions with small molecules such as toxins, vitamins, and natural biochemicals at precisions of 1-5% . Micro-proton-induced-xray-emission quantifies elemental abundancesmore » in separated metalloprotein samples to nanogram amounts and is capable of quantifying phosphorylated loci in gels. Accelerator-based quantitation is a possible tool for quantifying the genome translation into proteome.« less

Comparative Salivary Proteome of Hepatitis B- and C-Infected Patients

PubMed Central

Gonçalves, Lorena Da Rós; Campanhon, Isabele Batista; Domingues, Romênia R.; Paes Leme, Adriana F.; Soares da Silva, Márcia Regina

2014-01-01

Hepatitis B and C virus (HBV and HCV) infections are an important cause of cirrhosis and hepatocellular carcinoma. The natural history has a prominent latent phase, and infected patients may remain undiagnosed; this situation may lead to the continuing spread of these infections in the community. Compelling reasons exist for using saliva as a diagnostic fluid because it meets the demands of being an inexpensive, noninvasive and easy-to-use diagnostic method. Indeed, comparative analysis of the salivary proteome using mass spectrometry is a promising new strategy for identifying biomarkers. Our goal is to apply an Orbitrap-based quantitative approach to explore the salivary proteome profile in HBV- and HCV-infected patients. In the present study, whole saliva was obtained from 20 healthy, (control) 20 HBV-infected and 20 HCV-infected subjects. Two distinct pools containing saliva from 10 subjects of each group were obtained. The samples were ultracentrifuged and fractionated, and all fractions were hydrolyzed (trypsin) and injected into an LTQ-VELOS ORBITRAP. The identification and analyses of peptides were performed using Proteome Discoverer1.3 and ScaffoldQ + v.3.3.1. From a total of 362 distinct proteins identified, 344 proteins were identified in the HBV, 326 in the HCV and 303 in the control groups. Some blood proteins, such as flavin reductase (which converts biliverdin to bilirubin), were detected only in the HCV group. The data showed a reduced presence of complement C3, ceruloplasmin, alpha(1)-acid glycoprotein and alpha(2)-acid glycoprotein in the hepatitis-infected patients. Peptides of serotransferrin and haptoglobin were less detected in the HCV group. This study provides an integrated perspective of the salivary proteome, which should be further explored in future studies targeting specific disease markers for HBV and HCV infection. PMID:25423034

Developmental distribution of the plasma membrane-enriched proteome in the maize primary root growth zone.

PubMed

Zhang, Zhe; Voothuluru, Priyamvada; Yamaguchi, Mineo; Sharp, Robert E; Peck, Scott C

2013-01-01

Within the growth zone of the maize primary root, there are well-defined patterns of spatial and temporal organization of cell division and elongation. However, the processes underlying this organization remain poorly understood. To gain additional insights into the differences amongst the defined regions, we performed a proteomic analysis focusing on fractions enriched for plasma membrane (PM) proteins. The PM is the interface between the plant cell and the apoplast and/or extracellular space. As such, it is a key structure involved in the exchange of nutrients and other molecules as well as in the integration of signals that regulate growth and development. Despite the important functions of PM-localized proteins in mediating these processes, a full understanding of dynamic changes in PM proteomes is often impeded by low relative concentrations relative to total proteins. Using a relatively simple strategy of treating microsomal fractions with Brij-58 detergent to enrich for PM proteins, we compared the developmental distribution of proteins within the root growth zone which revealed a number of previously known as well as novel proteins with interesting patterns of abundance. For instance, the quantitative proteomic analysis detected a gradient of PM aquaporin proteins similar to that previously reported using immunoblot analyses, confirming the veracity of this strategy. Cellulose synthases increased in abundance with increasing distance from the root apex, consistent with expected locations of cell wall deposition. The similar distribution pattern for Brittle-stalk-2-like protein implicates that this protein may also have cell wall related functions. These results show that the simplified PM enrichment method previously demonstrated in Arabidopsis can be successfully applied to completely unrelated plant tissues and provide insights into differences in the PM proteome throughout growth and development zones of the maize primary root.

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