Sigpep: calculating unique peptide signature transition sets in a complete proteome background.

We have created a new software platform called sigpep that analyzes transition redundancy in selected reaction monitoring assays. Building on this platform, we also created a web application to generate transition sets with unique signatures for targeted peptides. The platform has been made available under the permissive Apache 2.0 open-source license, and the web application can be accessed from http://iomics.ugent.be/sigpep.

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.

Mass spectrometry-driven proteomics: an introduction.

Proteins are reckoned to be the key actors in a living organism. By studying proteins, one engages into deciphering a complex series of events occurring during a protein's life span. This starts at the creation of a protein, which is tightly controlled on both a transcriptional (Williams and Tyler, 2007, Curr Opin Genet Dev 17, 88-93) and a translational level (Van Der Kelen et al., 2009, Crit Rev Biochem Mol Biol 44, 143-168). During translation, a primary strand of amino acids undergoes a complex folding process in order to obtain a native three-dimensional protein structure (Gross et al., 2003, Cell 115, 739-750). Proteins take on a plethora of functions, such as complex formation, receptor activity, and signal transduction, which ultimately adds up to a cellular phenotype. Consequently, protein analysis is of major interest in molecular biology and involves annotating their presence and localization, as well as their modification state and biochemical context. To accomplish this, many methods have been developed over the last decades, and their general principles and important recent advances in large-scale protein analysis or proteomics are discussed in this review.

A stringent approach to improve the quality of nitrotyrosine peptide identifications.

Tyrosine nitration is the consequence of a complex machinery of formation and merging of oxygen and nitrogen radicals, and has been associated with both physiological pathways as well as with several human diseases. The latter turned this posttranslational protein modification into an interesting biomarker, being either a consequence of the disease or a factor contributing to the disease onset. However, the interpretation of MS and MS/MS data of peptides containing nitrotyrosine has proven to be very challenging and consequently, the risk of linking MS/MS spectra to incorrect peptide sequences exists and has been reported. Here, we discuss the causes of data misinterpretation and describe a general method to avoid mistakes of MS/MS spectrum misinterpretation. Central in our approach is the reduction of nitrotyrosine into aminotyrosine and the use of the Peptizer algorithm to inspect MS/MS quality-related assumptions.

Probing the efficiency of proteolytic events by positional proteomics.

Several mass spectrometry-driven techniques allow to map the substrate repertoires and specificities of proteases. These techniques typically yield long lists of protease substrates and processed sites with (potential) physiological relevance, but in order to understand the primary function of a protease, it is important to discern bystander substrates from critical substrates. Because the former are generally processed with lower efficiency, data on the actual substrate cleavage efficiency could assist in categorizing protease substrates. In this study, quantitative mass spectrometry following metabolic proteome labeling (SILAC), combined with the isolation of N-terminal peptides by Combined Fractional Diagonal Chromatography, was used to monitor fluxes in the concentration of protease-generated neo-N-termini. In our experimental setup, a Jurkat cell lysate was treated with the human serine protease granzyme B (hGrB) for three different incubation periods. The extensive list of human granzyme B substrates previously catalogued by N-terminal Combined Fractional Diagonal Chromatography (1) was then used to assign 101 unique hGrB-specific neo-N-termini in 86 proteins. In this way, we were able to define several sites as getting efficiently cleaved in vitro and consequently recognize potential physiologically more relevant substrates. Among them the well-known hGrB substrate Bid was confirmed as being an efficient hGrB substrate next to several other potential regulators of hGrB induced apoptosis such as Bnip2 and Akap-8. Several of our proteomics results were further confirmed by substrate immunoblotting and by using peptide substrates incubated with human granzyme B.

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.

Proteome-wide substrate analysis indicates substrate exclusion as a mechanism to generate caspase-7 versus caspase-3 specificity.

Caspase-3 and -7 are considered functionally redundant proteases with similar proteolytic specificities. We performed a proteome-wide screen on a mouse macrophage lysate using the N-terminal combined fractional diagonal chromatography technology and identified 46 shared, three caspase-3-specific, and six caspase-7-specific cleavage sites. Further analysis of these cleavage sites and substitution mutation experiments revealed that for certain cleavage sites a lysine at the P5 position contributes to the discrimination between caspase-7 and -3 specificity. One of the caspase-7-specific substrates, the 40 S ribosomal protein S18, was studied in detail. The RPS18-derived P6-P5' undecapeptide retained complete specificity for caspase-7. The corresponding P6-P1 hexapeptide still displayed caspase-7 preference but lost strict specificity, suggesting that P' residues are additionally required for caspase-7-specific cleavage. Analysis of truncated peptide mutants revealed that in the case of RPS18 the P4-P1 residues constitute the core cleavage site but that P6, P5, P2', and P3' residues critically contribute to caspase-7 specificity. Interestingly, specific cleavage by caspase-7 relies on excluding recognition by caspase-3 and not on increasing binding for caspase-7.

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.

Peptizer, a tool for assessing false positive peptide identifications and manually validating selected results.

False positive peptide identifications are a major concern in the field of peptidecentric, mass spectrometry-driven gel-free proteomics. They occur in regions where the score distributions of true positives and true negatives overlap. Removal of these false positive identifications necessarily involves a trade-off between sensitivity and specificity. Existing postprocessing tools typically rely on a fixed or semifixed set of assumptions in their attempts to optimize both the sensitivity and the specificity of peptide and protein identification using MS/MS spectra. Because of the expanding diversity in available proteomics technologies, however, these postprocessing tools often struggle to adapt to emerging technology-specific peculiarity. Here we present a novel tool named Peptizer that solves this adaptability issue by making use of pluggable assumptions. This research-oriented postprocessing tool also includes a graphical user interface to perform efficient manual validation of suspect identifications for optimal sensitivity recovery. Peptizer is open source software under the Apache2 license and is written in Java.

Implementation and application of a versatile clustering tool for tandem mass spectrometry data.

High-throughput proteomics experiments typically generate large amounts of peptide fragmentation mass spectra during a single experiment. There is often a substantial amount of redundant fragmentation of the same precursors among these spectra, which is usually considered a nuisance. We here discuss the potential of clustering and merging redundant spectra to turn this redundancy into a useful property of the dataset. To this end, we have created the first general-purpose, freely available open-source software application for clustering and merging MS/MS spectra. The application also introduces a novel approach to calculating the similarity of fragmentation mass spectra that takes into account the increased precision of modern mass spectrometers, and we suggest a simple but effective improvement to single-linkage clustering. The application and the novel algorithms are applied to several real-life proteomic datasets and the results are discussed. An analysis of the influence of the different algorithms available and their parameters is given, as well as a number of important applications of the overall approach.

Assessing a novel microfluidic interface for shotgun proteome analyses.

Microfluidic interfaces coupled to ESI mass spectrometers hold great potential for proteomics as they have been shown to augment the overall sensitivity of measurements and require only a minimum of operator manipulations as compared to conventional nano-LC interfaces. Here, we evaluated a new type of HPLC-Chips holding larger enrichment columns (thus an increased sample loading capacity) for gel-free proteome studies. A tryptic digest of a human T-cell proteome was fractionated by strong cation exchange chromatography and selected fractions were analyzed by MS/MS on an IT mass spectrometer using both the new HPLC-Chip as well as a conventional nano-LC-MS/MS interface. Our results indicate that the HPLC-Chip is capable of handling very complex peptide mixtures and, in fact, leads to the identification of more peptides and proteins as compared to when a conventional interface was used. The HPLC-Chip preferentially produced doubly charged tryptic peptides. We further show that MS/MS spectra of doubly charged tryptic peptide ions are more readily identified by MASCOT as compared to those from triply charged precursors and thus argue that besides the improved chromatographic conditions provided by the HPLC-Chip, its peptide charging profile might be a secondary factor leading to an increased proteome coverage.