The iceLogo web server and SOAP service for determining protein consensus sequences.

The iceLogo web server and SOAP service implement the previously published iceLogo algorithm. iceLogo builds on probability theory to visualize protein consensus sequences in a format resembling sequence logos. Peptide sequences are compared against a reference sequence set that can be tailored to the studied system and the used protocol. As such, not only over- but also underrepresented residues can be visualized in a statistically sound manner, which further allows the user to easily analyse and interpret conserved sequence patterns in proteins. The web application and SOAP service can be found free and open to all users without the need for a login on http://iomics.ugent.be/icelogoserver/main.html.

The Online Protein Processing Resource (TOPPR): a database and analysis platform for protein processing events.

We here present The Online Protein Processing Resource (TOPPR; http://iomics.ugent.be/toppr/), an online database that contains thousands of published proteolytically processed sites in human and mouse proteins. These cleavage events were identified with COmbinded FRActional DIagonal Chromatography proteomics technologies, and the resulting database is provided with full data provenance. Indeed, TOPPR provides an interactive visual display of the actual fragmentation mass spectrum that led to each identification of a reported processed site, complete with fragment ion annotations and search engine scores. Apart from warehousing and disseminating these data in an intuitive manner, TOPPR also provides an online analysis platform, including methods to analyze protease specificity and substrate-centric analyses. Concretely, TOPPR supports three ways to retrieve data: (i) the retrieval of all substrates for one or more cellular stimuli or assays; (ii) a substrate search by UniProtKB/Swiss-Prot accession number, entry name or description; and (iii) a motif search that retrieves substrates matching a user-defined protease specificity profile. The analysis of the substrates is supported through the presence of a variety of annotations, including predicted secondary structure, known domains and experimentally obtained 3D structure where available. Across substrates, substrate orthologs and conserved sequence stretches can also be shown, with iceLogo visualization provided for the latter.

Combining quantitative proteomics data processing workflows for greater sensitivity.

We here describe a normalization method to combine quantitative proteomics data. By merging the output of two popular quantification software packages, we obtained a 20% increase (on average) in the number of quantified human proteins without suffering from a loss of quality. Our integrative workflow is freely available through our user-friendly, open-source Rover software (http://compomics-rover.googlecode.com/).

Cells lacking ß-actin are genetically reprogrammed and maintain conditional migratory capacity.

Vertebrate nonmuscle cells express two actin isoforms: cytoplasmic ß- and γ-actin. Because of the presence and localized translation of ß-actin at the leading edge, this isoform is generally accepted to specifically generate protrusive forces for cell migration. Recent evidence also implicates ß-actin in gene regulation. Cell migration without ß-actin has remained unstudied until recently and it is unclear whether other actin isoforms can compensate for this cytoplasmic function and/or for its nuclear role. Primary mouse embryonic fibroblasts lacking ß-actin display compensatory expression of other actin isoforms. Consistent with this preservation of polymerization capacity, ß-actin knockout cells have unchanged lamellipodial protrusion rates despite a severe migration defect. To solve this paradox we applied quantitative proteomics revealing a broad genetic reprogramming of ß-actin knockout cells. This also explains why reintroducing ß-actin in knockout cells does not restore the affected cell migration. Pathway analysis suggested increased Rho-ROCK signaling, consistent with observed phenotypic changes. We therefore developed and tested a model explaining the phenotypes in ß-actin knockout cells based on increased Rho-ROCK signaling and increased TGFß production resulting in increased adhesion and contractility in the knockout cells. Inhibiting ROCK or myosin restores migration of ß-actin knockout cells indicating that other actins compensate for ß-actin in this process. Consequently, isoactins act redundantly in providing propulsive forces for cell migration, but ß-actin has a unique nuclear function, regulating expression on transcriptional and post-translational levels, thereby preventing myogenic differentiation.

Complementary positional proteomics for screening substrates of endo- and exoproteases.

We describe a positional proteomics approach to simultaneously analyze N- and C-terminal peptides and used it to screen for human protein substrates of granzyme B and carboxypeptidase A4 in human cell lysates. This approach allowed comprehensive proteome studies, and we report the identification of 965 database-annotated protein C termini, 334 neo-C termini resulting from granzyme B processing and 16 neo-C termini resulting from carboxypeptidase A4 processing.

Redox proteomics of protein-bound methionine oxidation.

We here present a new method to measure the degree of protein-bound methionine sulfoxide formation at a proteome-wide scale. In human Jurkat cells that were stressed with hydrogen peroxide, over 2000 oxidation-sensitive methionines in more than 1600 different proteins were mapped and their extent of oxidation was quantified. Meta-analysis of the sequences surrounding the oxidized methionine residues revealed a high preference for neighboring polar residues. Using synthetic methionine sulfoxide containing peptides designed according to the observed sequence preferences in the oxidized Jurkat proteome, we discovered that the substrate specificity of the cellular methionine sulfoxide reductases is a major determinant for the steady-state of methionine oxidation. This was supported by a structural modeling of the MsrA catalytic center. Finally, we applied our method onto a serum proteome from a mouse sepsis model and identified 35 in vivo methionine oxidation events in 27 different proteins.

Proteome profiling of the green sulfur bacterium Chlorobaculum tepidum by N-terminal proteomics.

In this study, we performed the first large-scale identification of N-terminal peptides from the green sulfur bacterium Chlorobaculum tepidum. Combined fractional diagonal chromatography (COFRADIC) was used to isolate protein N-terminal peptides from three different proteome preparations, and following LC-MS/MS analysis, over 621 different proteins were identified by their N-terminal peptides. Our data constitute the largest data set currently available for protein N-termini of prokaryotic photosynthetic organisms.

A quantitative proteomics design for systematic identification of protease cleavage events.

We present here a novel proteomics design for systematic identification of protease cleavage events by quantitative N-terminal proteomics, circumventing the need for time-consuming manual validation. We bypass the singleton detection problem of protease-generated neo-N-terminal peptides by introducing differential isotopic proteome labeling such that these substrate reporter peptides are readily distinguished from all other N-terminal peptides. Our approach was validated using the canonical human caspase-3 protease and further applied to mouse cathepsin D and E substrate processing in a mouse dendritic cell proteome, identifying the largest set of protein protease substrates ever reported and gaining novel insight into substrate specificity differences of these cathepsins.

Proteomics analyses reveal the evolutionary conservation and divergence of N-terminal acetyltransferases from yeast and humans.

N(alpha)-terminal acetylation is one of the most common protein modifications in eukaryotes. The COmbined FRActional DIagonal Chromatography (COFRADIC) proteomics technology that can be specifically used to isolate N-terminal peptides was used to determine the N-terminal acetylation status of 742 human and 379 yeast protein N termini, representing the largest eukaryotic dataset of N-terminal acetylation. The major N-terminal acetyltransferase (NAT), NatA, acts on subclasses of proteins with Ser-, Ala-, Thr-, Gly-, Cys- and Val- N termini. NatA is composed of subunits encoded by yARD1 and yNAT1 in yeast and hARD1 and hNAT1 in humans. A yeast ard1-Delta nat1-Delta strain was phenotypically complemented by hARD1 hNAT1, suggesting that yNatA and hNatA are similar. However, heterologous combinations, hARD1 yNAT1 and yARD1 hNAT1, were not functional in yeast, suggesting significant structural subunit differences between the species. Proteomics of a yeast ard1-Delta nat1-Delta strain expressing hNatA demonstrated that hNatA acts on nearly the same set of yeast proteins as yNatA, further revealing that NatA from humans and yeast have identical or nearly identical specificities. Nevertheless, all NatA substrates in yeast were only partially N-acetylated, whereas the corresponding NatA substrates in HeLa cells were mainly completely N-acetylated. Overall, we observed a higher proportion of N-terminally acetylated proteins in humans (84%) as compared with yeast (57%). N-acetylation occurred on approximately one-half of the human proteins with Met-Lys- termini, but did not occur on yeast proteins with such termini. Thus, although we revealed different N-acetylation patterns in yeast and humans, the major NAT, NatA, acetylates the same substrates in both species.

A comparison of MS2-based label-free quantitative proteomic techniques with regards to accuracy and precision.

The advent of algorithms for fragmentation spectrum-based label-free quantitative proteomics has enabled straightforward quantification of shotgun proteomic experiments. Despite the popularity of these approaches, few studies have been performed to assess their performance. We have therefore profiled the precision and the accuracy of three distinct relative label-free methods on both the protein and the proteome level. We derived our test data from two well-characterized publicly available quantitative data sets.

A reproducibility-based evaluation procedure for quantifying the differences between MS/MS peak intensity normalization methods.

The identification of peptides and proteins from fragmentation mass spectra is a very common approach in the field of proteomics. Contemporary high-throughput peptide identification pipelines can quickly produce large quantities of MS/MS data that contain valuable knowledge about the actual physicochemical processes involved in the peptide fragmentation process, which can be extracted through extensive data mining studies. As these studies attempt to exploit the intensity information contained in the MS/MS spectra, a critical step required for a meaningful comparison of this information between MS/MS spectra is peak intensity normalization. We here describe a procedure for quantifying the efficiency of different published normalization methods in terms of the quartile coefficient of dispersion (qcod) statistic. The quartile coefficient of dispersion is applied to measure the dispersion of the peak intensities between redundant MS/MS spectra, allowing the quantification of the differences in computed peak intensity reproducibility between the different normalization methods. We demonstrate that our results are independent of the data set used in the evaluation procedure, allowing us to provide generic guidance on the choice of normalization method to apply in a certain MS/MS pipeline application.

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

BACKGROUND: The 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. RESULTS: In 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. CONCLUSIONS: As 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.

RIBAR and xRIBAR: Methods for reproducible relative MS/MS-based label-free protein quantification.

Mass spectrometry-driven proteomics is increasingly relying on quantitative analyses for biological discoveries. As a result, different methods and algorithms have been developed to perform relative or absolute quantification based on mass spectrometry data. One of the most popular quantification methods are the so-called label-free approaches, which require no special sample processing, and can even be applied retroactively to existing data sets. Of these label-free methods, the MS/MS-based approaches are most often applied, mainly because of their inherent simplicity as compared to MS-based methods. The main application of these approaches is the determination of relative protein amounts between different samples, expressed as protein ratios. However, as we demonstrate here, there are some issues with the reproducibility across replicates of these protein ratio sets obtained from the various MS/MS-based label-free methods, indicating that the existing methods are not optimally robust. We therefore present two new methods (called RIBAR and xRIBAR) that use the available MS/MS data more effectively, achieving increased robustness. Both the accuracy and the precision of our novel methods are analyzed and compared to the existing methods to illustrate the increased robustness of our new methods over existing ones.

Analysis of the resolution limitations of peptide identification algorithms.

Proteome identification using peptide-centric proteomics techniques is a routinely used analysis technique. One of the most powerful and popular methods for the identification of peptides from MS/MS spectra is protein database matching using search engines. Significance thresholding through false discovery rate (FDR) estimation by target/decoy searches is used to ensure the retention of predominantly confident assignments of MS/MS spectra to peptides. However, shortcomings have become apparent when such decoy searches are used to estimate the FDR. To study these shortcomings, we here introduce a novel kind of decoy database that contains isobaric mutated versions of the peptides that were identified in the original search. Because of the supervised way in which the entrapment sequences are generated, we call this a directed decoy database. Since the peptides found in our directed decoy database are thus specifically designed to look quite similar to the forward identifications, the limitations of the existing search algorithms in making correct calls in such strongly confusing situations can be analyzed. Interestingly, for the vast majority of confidently identified peptide identifications, a directed decoy peptide-to-spectrum match can be found that has a better or equal match score than the forward match score, highlighting an important issue in the interpretation of peptide identifications in present-day high-throughput proteomics.

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

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.

Analysis of protein processing by N-terminal proteomics reveals novel species-specific substrate determinants of granzyme B orthologs.

Using a targeted peptide-centric proteomics approach, we performed in vitro protease substrate profiling of the apoptotic serine protease granzyme B resulting in the delineation of more than 800 cleavage sites in 322 human and 282 mouse substrates, encompassing the known substrates Bid, caspase-7, lupus La protein, and fibrillarin. Triple SILAC (stable isotope labeling by amino acids in cell culture) further permitted intra-experimental evaluation of species-specific variations in substrate selection by the mouse or human granzyme B ortholog. For the first time granzyme B substrate specificities were directly mapped on a proteomic scale and revealed unknown cleavage specificities, uncharacterized extended specificity profiles, and macromolecular determinants in substrate selection that were confirmed by molecular modeling. We further tackled a substrate hunt in an in vivo setup of natural killer cell-mediated cell death confirming in vitro characterized granzyme B cleavages next to several other unique and hitherto unreported proteolytic events in target cells.

In vitro and in vivo protein-bound tyrosine nitration characterized by diagonal chromatography.

A new proteomics technique for analyzing 3-nitrotyrosine-containing peptides is presented here. This technique is based on the combined fractional diagonal chromatography peptide isolation procedures by which specific classes of peptides are isolated following a series of identical reverse-phase HPLC separation steps. Here dithionite is used to reduce 3-nitrotyrosine to 3-aminotyrosine peptides, which thereby become more hydrophilic. Our combined fractional diagonal chromatography technique was first applied to characterize tyrosine nitration in tetranitromethane-modified BSA and further led to a high quality list of 335 tyrosine nitration sites in 267 proteins in a peroxynitrite-treated lysate of human Jurkat cells. We then analyzed a serum sample of a C57BL6/J mouse in which septic shock was induced by intravenous Salmonella infection and identified six in vivo nitration events in four serum proteins, thereby illustrating that our technique is sufficiently sensitive to identify rare in vivo tyrosine nitration sites in a very complex background.

Rover: a tool to visualize and validate quantitative proteomics data from different sources.

Manual validation of regulated proteins found in MS-driven quantitative proteome studies is tedious. Here we present Rover (http://genesis.ugent.be/rover), a tool that facilitates this process. Rover accepts quantitative data from different sources such as MASCOT Distiller and MaxQuant and, in an intuitive environment, Rover visualizes these data such that the user can select and validate algorithm-suggested regulated proteins in the frame of the whole experiment and in the context of the protein inference problem.

MS-driven protease substrate degradomics.

Proteolytic processing has recently received increased attention in the field of signal propagation and cellular differentiation. Because of its irreversible nature, protein cleavage has been associated with committed steps in cell function. One aspect of protease biology that boomed the past few years is the detailed characterization of protease substrates by both shotgun as well as targeted MS-driven proteomics techniques. The most promising techniques are discussed in this review and we further elaborate on the bioinformatics challenges that accompany mainly qualitative, MS-driven protease substrate degradome studies.

ms_lims, a simple yet powerful open source laboratory information management system for MS-driven proteomics.

MS-based proteomics produces large amounts of mass spectra that require processing, identification and possibly quantification before interpretation can be undertaken. High-throughput studies require automation of these various steps, and management of the data in association with the results obtained. We here present ms_lims (http://genesis.UGent.be/ms_lims), a freely available, open-source system based on a central database to automate data management and processing in MS-driven proteomics analyses.