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.

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.

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

Vertebrate nonmuscle cells express two actin isoforms: cytoplasmic β- and γ-actin. Because of the presence and localized translation of β-actin at the leading edge, this isoform is generally accepted to specifically generate protrusive forces for cell migration. Recent evidence also implicates β-actin in gene regulation.

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.

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.

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.

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.

A case study on the comparison of different software tools for automated quantification of peptides.

MS-driven proteomics has evolved over the past two decades to a high tech and high impact research field. Two distinct factors clearly influenced its expansion: the rapid growth of an arsenal of instrument and proteomic techniques that led to an explosion of high quality data and the development of software tools to analyze and interpret these data which boosted the number of scientific discoveries. In analogy with the benchmarking of new instruments and proteomic techniques, such software tools must be thoroughly tested and analyzed.

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.

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.

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.

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.

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.

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.

The substrate specificity profile of human granzyme A.

The exact biological function of granzyme A, a granule-associated serine protease belonging to the tryptase family of proteases, is still a matter of debate because conflicting roles have been suggested, such as initiation of caspase-independent apoptosis-like cell death and endogenous modulation of inflammatory processes. In contrast to its well-studied family member, granzyme B, far less is known about the physiological targets of granzyme A. Using an N-terminal peptide-centric proteomics technology, the substrate specificity of human granzyme A was extensively characterized at the level of macromolecular protein substrates.

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.

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.

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.

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.

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.

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.

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.