Marc Vaudel

The first comprehensive and quantitative analysis of human platelet protein composition allows the comparative analysis of structural and functional pathways

Antiplatelet treatment is of fundamental importance in combatting functions/dysfunction of platelets in the pathogenesis of cardiovascular and inflammatory diseases. Dysfunction of anucleate platelets is likely to be completely attributable to alterations in posttranslational modifications and protein expression. We therefore examined the proteome of platelets highly purified from fresh blood donations, using elaborate protocols to ensure negligible contamination by leukocytes, erythrocytes, and plasma. Using quantitative mass spectrometry, we created the first comprehensive and quantitative human platelet proteome, comprising almost 4000 unique proteins, estimated copy numbers for ∼ 3700 of those, and assessed intersubject (4 donors) as well as intrasubject (3 different blood samples from 1 donor) variations of the proteome. For the first time, our data allow for a systematic and weighted appraisal of protein networks and pathways in human platelets, and indicate the feasibility of differential and comprehensive proteome analyses from small blood donations. Because 85% of the platelet proteome shows no variation between healthy donors, this study represents the starting point for disease-oriented platelet proteomics. In the near future, comprehensive and quantitative comparisons between normal and well-defined dysfunctional platelets, or between platelets obtained from donors at various stages of chronic cardiovascular and inflammatory diseases will be feasible.

PeptideShaker enables reanalysis of MS-derived proteomics data sets

VOLUME 33 NUMBER 1 JANUARY 2015 NATURE BIOTECHNOLOGY methods (Supplementary Note 1). The reliability of all statistical metrics has been validated in detail using the complex Pyrococcus furiosus standard with an entrapment database for FDR accuracy verification14 (Supplementary Note 1). PeptideShaker’s user-oriented interface is divided into nine linked tabs, such that selections in any one tab are automatically propagated to the other tabs. The initial display is the ‘Overview’ tab (Fig. 2), which shows a single interactive view that includes identified proteins, peptides and spectra. Additional tabs feature specific aspects of a typical proteomics analysis pipeline, including spectrum identification details (with an emphasis on multiple search engine comparison), protein fractionation analysis, modification site localization analysis, protein three-dimensional structures (with mapped modifications), link to functional annotation resources, gene ontology analysis, identification validation and quality control (Supplementary Note 1). Numerous visualizations are provided in PeptideShaker to help the user understand the significance of the underlying data. For example, the software takes advantage of the identification multiplicity typical of proteomics experiments by visualizing multiple recorded PSMs15 for a given peptide or by displaying posttranslational modification localization both within and across spectra (Supplementary Note 1). Moreover, PeptideShaker provides chromosome and gene mapping, modification analysis and intuitive coverage annotation on the sequence of every identified protein, meeting the goals of the Human Proteome Project16. Results from PeptideShaker can be readily submitted to PRIDE and ProteomeXchange using the built-in PRIDE and mzIdentML17 exports; at the time of writing, this has already resulted in 52 publicly available PeptideShaker-derived ProteomeXchange assays. Other export options include spreadsheet-compatible text files, a descriptive certificate of analysis, highresolution image formats for all displayed graphics, exports to common graph database formats including Cytoscape (http:// cytoscape.org), and export to the widely used Nonlinear (http://www.nonlinear.com) Progenesis liquid chromatography (LC)-MS package for label-free quantification. To the Editor: Mass spectrometry (MS)-based proteomics is commonly used to identify and quantify the hundreds to thousands of proteins that are present in complex biological samples. Widespread data sharing via publicly accessible repositories, such as PRIDE1, has now become standard practice, aided by robust user-oriented tools for data submission2,3 and inspection4 and bolstered by the advent of the ProteomeXchange initiative5. Importantly, repository data sharing has enabled the first high-profile studies in which the repurposing of publicly available proteomics data has revealed new biological insights6,7. However, proteomics data processing and (re-)analysis currently remain far from routine practice. There is a pressing need for a user-friendly, open source tool that empowers users to carry out state-of-the-art proteomics data analysis at any stage in the data life cycle8,9. To maximize the value of public proteomics data, reuse and repurposing must become straightforward, allowing the completion of the proteomics data cycle. Here we describe PeptideShaker (http://peptideshaker.googlecode.com), a proteomics informatics software that can be used at any stage in the proteomics data cycle for the analysis and interpretation of primary data, enabling data sharing and dissemination and re-analysis of publicly available proteomics data. Importantly, PeptideShaker can work with the combined output of multiple identification algorithms (Fig. 1). To identify peptides and proteins PeptideShaker uses the target-decoy search strategy10 to estimate posterior error probabilities and uses these to unify the peptide-to-spectrum match (PSM) lists of different search engines, thus increasing the confidence and sensitivity of hits compared with single-search-engine processing11,12. PeptideShaker provides statistical confidence estimates for each peptide and protein, taking into account protein inference issues13. Furthermore, as well as providing false discovery rates (FDRs) at the PSM, peptide and protein levels, PeptideShaker calculates reliable false negative rates (FNRs), providing the user with a novel and highly useful interface to filter results according to an FDR-versus-FNR cost-benefit rationale that has so far been absent from proteomics. This filter for specificity and sensitivity includes interactive graphs providing immediate feedback on the values of FDR and FNR for PSMs, peptides and proteins at any chosen threshold. In addition to these identification reliability measures, PeptideShaker also provides confident modification site inference using the latest localization PeptideShaker enables reanalysis of MS-derived proteomics data sets

SearchGUI: An open-source graphical user interface for simultaneous OMSSA and X!Tandem searches

The identification of proteins by mass spectrometry is a standard technique in the field of proteomics, relying on search engines to perform the identifications of the acquired spectra. Here, we present a user‐friendly, lightweight and open‐source graphical user interface called SearchGUI (http://searchgui.googlecode.com), for configuring and running the freely available OMSSA (open mass spectrometry search algorithm) and X!Tandem search engines simultaneously. Freely available under the permissible Apache2 license, SearchGUI is supported on Windows, Linux and OSX.

Peptide and protein quantification: A map of the minefield

The increasing popularity of gel‐free proteomics technologies has created a strong demand for compatible quantitative analysis methods. As a result, a plethora of different techniques has been proposed to perform gel‐free quantitative analysis of proteomics samples. Each of these methods comes with certain strengths and shortcomings, and they often are dedicated to a specific purpose. This review will present a brief overview of the main methods, organized by their underlying concepts, and will discuss the issues they raise with a focus on data processing. Finally, we will list the available software that can help with the data processing from quantitative experiments. We hope that this review will thus enable researchers to find the most appropriate method available for their research objectives, and can also serve as a basis for creating a reliable data processing strategy.

compomics-utilities: an open-source Java library for computational proteomics

BackgroundThe growing interest in the field of proteomics has increased the demand for software tools and applications that process and analyze the resulting data. And even though the purpose of these tools can vary significantly, they usually share a basic set of features, including the handling of protein and peptide sequences, the visualization of (and interaction with) spectra and chromatograms, and the parsing of results from various proteomics search engines. Developers typically spend considerable time and effort implementing these support structures, which detracts from working on the novel aspects of their tool.ResultsIn order to simplify the development of proteomics tools, we have implemented an open-source support library for computational proteomics, called compomics-utilities. The library contains a broad set of features required for reading, parsing, and analyzing proteomics data. compomics-utilities is already used by a long list of existing software, ensuring library stability and continued support and development.ConclusionsAs a user-friendly, well-documented and open-source library, compomics-utilities greatly simplifies the implementation of the basic features needed in most proteomics tools. Implemented in 100% Java, compomics-utilities is fully portable across platforms and architectures. Our library thus allows the developers to focus on the novel aspects of their tools, rather than on the basic functions, which can contribute substantially to faster development, and better tools for proteomics.

Time-resolved characterization of cAMP/PKA-dependent signaling reveals that platelet inhibition is a concerted process involving multiple signaling pathways

One of the most important physiological platelet inhibitors is endothelium-derived prostacyclin which stimulates the platelet cyclic adenosine monophosphate/protein kinase A (cAMP/PKA)-signaling cascade and inhibits virtually all platelet-activating key mechanisms. Using quantitative mass spectrometry, we analyzed time-resolved phosphorylation patterns in human platelets after treatment with iloprost, a stable prostacyclin analog, for 0, 10, 30, and 60 seconds to characterize key mediators of platelet inhibition and activation in 3 independent biological replicates. We quantified over 2700 different phosphorylated peptides of which 360 were significantly regulated upon stimulation. This comprehensive and time-resolved analysis indicates that platelet inhibition is a multipronged process involving different kinases and phosphatases as well as many previously unanticipated proteins and pathways.

Current methods for global proteome identification.

In a time frame of a few decades, protein identification went from laborious single protein identification to automated identification of entire proteomes. This shift was enabled by the emergence of peptide-centric, gel-free analyses, in particular the so-called shotgun approaches, which not only rely on extensive experiments, but also on cutting-edge data processing methods. The present review therefore provides an overview of a shotgun proteomics identification workflow, listing the state-of-the-art methods involved and software that implement these. The authors focus on freely available tools where possible. Finally, data analysis in the context of emerging across-omics studies will also be discussed briefly, where proteomics goes beyond merely delivering a list of protein accession numbers.

XTandem Parser: An open-source library to parse and analyse X!Tandem MS/MS search results

Identification of proteins by MS plays an important role in proteomics. A crucial step concerns the identification of peptides from MS/MS spectra. The X!Tandem Project (http://www.thegpm.org/tandem) supplies an open‐source search engine for this purpose. In this study, we present an open‐source Java library called XTandem Parser that parses X!Tandem XML result files into an easily accessible and fully functional object model (http://xtandem‐parser.googlecode.com). In addition, a graphical user interface is provided that functions as a usage example and an end‐user visualization tool.

D-score: a search engine independent MD-score.

While peptides carrying PTMs are routinely identified in gel‐free MS, the localization of the PTMs onto the peptide sequences remains challenging. Search engine scores of secondary peptide matches have been used in different approaches in order to infer the quality of site inference, by penalizing the localization whenever the search engine similarly scored two candidate peptides with different site assignments. In the present work, we show how the estimation of posterior error probabilities for peptide candidates allows the estimation of a PTM score called the D‐score, for multiple search engine studies. We demonstrate the applicability of this score to three popular search engines: Mascot, OMSSA, and X!Tandem, and evaluate its performance using an already published high resolution data set of synthetic phosphopeptides. For those peptides with phosphorylation site inference uncertainty, the number of spectrum matches with correctly localized phosphorylation increased by up to 25.7% when compared to using Mascot alone, although the actual increase depended on the fragmentation method used. Since this method relies only on search engine scores, it can be readily applied to the scoring of the localization of virtually any modification at no additional experimental or in silico cost.

Peptide identification quality control

Identification of large proteomics data sets is routinely performed using sophisticated software tools called search engines. Yet despite the importance of the identification process, its configuration and execution is often performed according to established lab habits, and is mostly unsupervised by detailed quality control. In order to establish easily obtainable quality control criteria that can be broadly applied to the identification process, we here introduce several simple quality control methods. An unbiased quality control of identification parameters will be conducted using target/decoy searches providing significant improvement over identification standards. MASCOT identifications were for instance increased by 13% at a constant level of confidence. The target/decoy approach can however not be universally applied. We therefore also quality control the application of this strategy itself, providing useful and intuitive metrics for evaluating the precision and robustness of the obtained false discovery rate.