swissPIT: a novel approach for pipelined analysis of mass spectrometry data

The identification and characterization of peptides from tandem mass spectrometry (MS/MS) data represents a critical aspect of proteomics. Today, tandem MS analysis is often performed by only using a single identification program achieving identification rates between 10-50% (Elias and Gygi, 2007). Beside the development of new analysis tools, recent publications describe also the pipelining of different search programs to increase the identification rate (Hartler et al., 2007; Keller et al., 2005). The Swiss Protein Identification Toolbox (swissPIT) follows this approach, but goes a step further by providing the user an expandable multi-tool platform capable of executing workflows to analyze tandem MS-based data. One of the major problems in proteomics is the absent of standardized workflows to analyze the produced data. This includes the pre-processing part as well as the final identification of peptides and proteins. The main idea of swissPIT is not only the usage of different identification tool in parallel, but also the meaningful concatenation of different identification strategies at the same time. The swissPIT is open source software but we also provide a user-friendly web platform, which demonstrates the capabilities of our software and which is available at http://swisspit.cscs.ch upon request for account.     

LFQuant: A label‐free fast quantitative analysis tool for high‐resolution LC‐MS/MS proteomics data

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/ .     

Matrix‐assisted laser desorption/ionization time‐of‐flight mass spectrometry as a useful tool for the rapid identification of wild flea vectors preserved in alcohol

Flea identification is a significant issue because some species are considered as important vectors of several human pathogens that have emerged or re‐emerged recently, such as Bartonella henselae (Rhizobiales: Bartonellaceae) and Rickettsia felis (Rickettsiales: Rickettsiaceae). Matrix‐assisted laser desorption/ionization time‐of‐flight mass spectrometry (MALDI‐TOF MS) has been evaluated in recent years for the identification of multicellular organisms, including arthropods. A preliminary study corroborated the usefulness of this technique for the rapid identification of fleas, creating a preliminary database containing the spectra of five species of flea. However, longterm flea preservation in ethanol did not appear to be an adequate method of storage in the context of specimen identification by MALDI‐TOF MS profiling. The goal of the present work was to assess the performance of MALDI‐TOF MS in the identification of seven flea species [Ctenocephalides felis (Siphonaptera: Pulicidae), Ctenocephalides canis, Pulex irritans (Siphonaptera: Pulicidae), Archaeopsylla erinacei (Siphonaptera: Pulicidae), Leptopsylla taschenbergi (Siphonaptera: Ceratophyllidae), Stenoponia tripectinata (Siphonaptera: Stenoponiidae) and Nosopsyllus fasciatus (Siphonaptera: Ceratophyllidae)] collected in the field and stored in ethanol for different periods of time. The results confirmed that MALDI‐TOF MS can be used for the identification of wild fleas stored in ethanol. Furthermore, this technique was able to discriminate not only different flea genera, but also the two congeneric species C. felis and C. canis.     

Multivariate analysis of single quadrupole LC‐MS spectra for routine characterization and quantification of intact proteins

Modern high‐throughput proteomic platforms allow incomparable protein mixture resolution and identification. However, such sophisticated facilities are expensive and not always accessible for routine analysis of simple mixtures. In this paper, we propose a simple methodology, based on detection of intact, nondigested proteins by LC coupled to single quadrupole MS (sqLC‐MS), followed by the analysis of the resulting spectra by multivariate analysis (MA). By doing so, even large molecular weight (MW) proteins, generating complex spectra, can be characterized to a level that allows isoform discrimination, while standard algorithms, such as MS spectrum deconvolution, cannot. To demonstrate the effectiveness of the proposed approach, we have analyzed the spectra of a set of purified, intact albumins from seven different organisms (bovine, human, rabbit, rat, sheep, mouse, and pig) as a model of microheterogenous proteins, using Projection to Latent Structure Discriminant Analysis (PLS‐DA). Although these proteins are very similar (less than 1% difference in MW), sqLC‐MS/MA allowed their classification, and the identification of unknown source samples. In addition, MA allowed precise protein quantification from the same data (calibration curve R² = 0.9966). The ability to rapidly characterize and quantify proteins, together with simplicity and affordability, could make of combined sqLC‐MS/MA a routine method for the characterization of simple mixture of known proteins.     

A comparison of MS/MS‐based,stable‐isotope‐labeled,quantitation performance on ESI‐quadrupole TOF and MALDI‐TOF/TOF mass spectrometers

The peptide‐based quantitation accuracy and precision of LC‐ESI (QSTAR Elite) and LC‐MALDI (4800 MALDI TOF/TOF) were compared by analyzing identical Escherichia coli tryptic digests containing iTRAQ‐labeled peptides of defined abundances (1:1, 2.5:1, 5:1, and 10:1). Only 51.4% of QSTAR spectra were used for quantitation by ProteinPilot Software versus 66.7% of LC‐MALDI spectra. The average protein sequence coverages for LC‐ESI and LC‐MALDI were 24.0 and 18.2% (14.9 and 8.4 peptides per protein), respectively. The iTRAQ‐based expression ratios determined by ProteinPilot from the 57 467 ESI‐MS/MS and 26 085 MALDI‐MS/MS spectra were analyzed for measurement accuracy and reproducibility. When the relative abundances of peptides within a sample were increased from 1:1 to 10:1, the mean ratios calculated on both instruments differed by only 0.7–6.7% between platforms. In the 10:1 experiment, up to 64.7% of iTRAQ ratios from LC‐ESI MS/MS spectra failed S/N thresholds and were excluded from quantitation, while only 0.1% of the equivalent LC‐MALDI iTRAQ ratios were rejected. Re‐analysis of an archived LC‐MALDI sample set stored for 5 months generated 3715 MS/MS spectra for quantitation, compared with 3845 acquired originally, and the average ratios differed by only 3.1%. Overall, MS/MS‐based peptide quantitation performance of offline LC‐MALDI was comparable with on‐line LC‐ESI, which required threefold less time. However, offline LC‐MALDI allows the re‐analysis of archived HPLC‐separated samples.     

ITMSQ: A software tool for N‐ and C‐terminal fragment ion pairs based isobaric tandem mass spectrometry quantification

Tandem MS (MS2) quantification using the series of N‐ and C‐terminal fragment ion pairs generated from isobaric‐labelled peptides was recently considered an accurate strategy in quantitative proteomics. However, the presence of multiplexed terminal fragment ion in MS2 spectra may reduce the efficiency of peptide identification, resulting in lower identification scores or even incorrect assignments. To address this issue, we developed a quantitative software tool, denoted isobaric tandem MS quantification (ITMSQ), to improve N‐ and C‐terminal fragment ion pairs based isobaric MS2 quantification. A spectrum splitting module was designed to separate the MS2 spectra from different samples, increasing the accuracy of both identification and quantification. ITMSQ offers a convenient interface through which parameters can be changed along with the labelling method, and the result files and all of the intermediate files can be exported. We performed an analysis of in vivo terminal amino acid labelling labelled HeLa samples and found that the numbers of quantified proteins and peptides increased by 13.64 and 27.52% after spectrum splitting, respectively. In conclusion, ITMSQ provides an accurate and reliable quantitative solutionfor N‐ and C‐terminal fragment ion pairs based isobaric MS2 quantitative methods.     

Comprehensive ADP‐ribosylome analysis identifies tyrosine as an ADP‐ribose acceptor site

Despite recent mass spectrometry (MS)‐based breakthroughs, comprehensive ADP‐ribose (ADPr)‐acceptor amino acid identification and ADPr‐site localization remain challenging. Here, we report the establishment of an unbiased, multistep ADP‐ribosylome data analysis workflow that led to the identification of tyrosine as a novel ARTD1/PARP1‐dependent in vivo ADPr‐acceptor amino acid. MS analyses of in vitro ADP‐ribosylated proteins confirmed tyrosine as an ADPr‐acceptor amino acid in RPS3A (Y155) and HPF1 (Y238) and demonstrated that trans‐modification of RPS3A is dependent on HPF1. We provide an ADPr‐site Localization Spectra Database (ADPr‐LSD), which contains 288 high‐quality ADPr‐modified peptide spectra, to serve as ADPr spectral references for correct ADPr‐site localizations.     

MS2‐Deisotoper: A Tool for Deisotoping High‐Resolution MS/MS Spectra in Normal and Heavy Isotope‐Labelled Samples

High‐resolution MS/MS spectra of peptides can be deisotoped to identify monoisotopic masses of peptide fragments. The use of such masses should improve protein identification rates. However, deisotoping is not universally used and its benefits have not been fully explored. Here, MS2‐Deisotoper, a tool for use prior to database search, is used to identify monoisotopic peaks in centroided MS/MS spectra. MS2‐Deisotoper works by comparing the mass and relative intensity of each peptide fragment peak to every other peak of greater mass, and by applying a set of rules concerning mass and intensity differences. After comprehensive parameter optimization, it is shown that MS2‐Deisotoper can improve the number of peptide spectrum matches (PSMs) identified by up to 8.2% and proteins by up to 2.8%. It is effective with SILAC and non‐SILAC MS/MS data. The identification of unique peptide sequences is also improved, increasing the number of human proteoforms by 3.7%. Detailed investigation of results shows that deisotoping increases Mascot ion scores, improves FDR estimation for PSMs, and leads to greater protein sequence coverage. At a peptide level, it is found that the efficacy of deisotoping is affected by peptide mass and charge. MS2‐Deisotoper can be used via a user interface or as a command‐line tool.     

Analysis of sesterterpenoids from Aspergillus terreus using ESI‐QTOF and ESI‐IT

Introduction – Biosynthesis of terretonin was studied due to the interesting skeleton of this series of sesterterpenoids. Very recently, López‐Gresa reported two new sesterterpenoids (terretonins E and F) which are inhibitors of the mammalian mitochondrial respiratory chain. Mass spectrometry (MS), especially tandem mass spectrometry, has been one of the most important physicochemical methods for the identification of trace natural products due to it rapidity, sensitivity and low levels of sample consumption. The potential application prospect and unique skeleton prompted us to study structural characterisation using MS. Objective – To obtain sufficient information for rapid structural elucidation of this class of compounds using MS. Methodology – The elemental composition of the product ions was confirmed by low‐energy ESI‐CID‐QTOF‐MS/MS analyses. The fragmentation pathways were postulated on the basis of ESI‐QTOF‐MS/MS/MS and ESI‐IT‐MSⁿ spectra. Common features and major differences between ESI‐QTOF‐MS/MS and IT‐MSⁿ spectra were compared. For ESI‐QTOF‐MS/MS/MS experiments, capillary exit voltage was raised to induce in‐source dissociation. Ammonium acetate or acetic acid were added into solutions to improve the intensity of [M + H]⁺. The collision energy was optimised to achieve sufficient fragmentation. Some fragmentation pathways were unambiguously proposed by the variety of abundance of fragment ions at different collision energies even without MSⁿ spectra. Results – Fragmentation pathways of five representative sesterterpenoids were elucidated using ESI‐QTOF‐MS/MS/MS and ESI‐IT‐MSⁿ in both positive‐ and negative‐ion mode. The key group of characterising fragmentation profiles was ring B, and these fragmentation patterns are helpful to identify different types of sestertepenoids. Conclusion – Complementary information obtained from fragmentation experiments of [M + H]⁺ (or [M + NH₄]⁺) and [M ? H]^? precursor ions is especially valuable for rapid identification of this kind of sesterterpenoid.     

Virtual Expert Mass Spectrometrist: iTRAQ tool for database‐dependent search,quantitation and result storage

A frequent goal of MS‐based proteomics experiments nowadays is to quantify changes in the abundance of proteins across several biological samples. The iTRAQ labeling method is a powerful technique; when combined with LC coupled to MS/MS it allows relative quantitation of up to eight different samples simultaneously. Despite the usefulness of iTRAQ current software solutions have limited functionality and require the combined use of several software programs for analysis of the data from different MS vendors. We developed an integrated tool, now available in the virtual expert mass spectrometrist (VEMS) program, for database‐dependent search of MS/MS spectra, quantitation and database storage for iTRAQ‐labeled samples. VEMS also provides useful alternative report types for large‐scale quantitative experiments. The implemented statistical algorithms build on quantitative algorithms previously used in proposed iTRAQ tools as described in detail herein. We propose a new algorithm, which provides more accurate peptide ratios for data that show an intensity‐dependent saturation. The accuracy of the proposed iTRAQ algorithm and the performance of VEMS are demonstrated by comparing results from VEMS, MASCOT and PEAKS Q obtained by analyzing data from a reference mixture of six proteins. Users can download VEMS and test data from “ http://www.portugene.com/software.html ”.     

Helicobacter pylori proteomics by 2‐DE/MS, 1‐DE‐LC/MS and functional data mining

With its predicted proteome of 1550 proteins (data set Etalon) Helicobacter pylori 26695 represents a perfect model system of medium complexity for investigating basic questions in proteomics. We analyzed urea‐solubilized proteins by 2‐DE/MS (data set 2‐DE) and by 1‐DE‐LC/MS (Supprot); proteins insoluble in 9 M urea but solubilized by SDS (Pellet); proteins precipitating in the Sephadex layer at the application side of IEF (Sephadex) by 1‐DE‐LC/MS; and proteins precipitating close to the application side within the IEF gel by LC/MS (Startline). The experimental proteomics data of H. pylori comprising 567 proteins (protein coverage: 36.6%) were stored in the Proteome Database System for Microbial Research ( http://www.mpiib‐berlin.mpg.de/2D‐PAGE/ ), which gives access to raw mass spectra (MALDI‐TOF/TOF) in T2D format, as well as to text files of peak lists. For data mining the protein mapping and comparison tool PROMPT ( http://webclu.bio.wzw.tum.de/prompt/ ) was used. The percentage of proteins with transmembrane regions, relative to all proteins detected, was 0, 0.2, 0, 0.5, 3.8 and 6.3% for 2‐DE, Supprot, Startline, Sephadex, Pellet, and Etalon, respectively. 2‐DE does not separate membrane proteins because they are insoluble in 9 M urea/70 mM DTT and 2% CHAPS. SDS solubilizes a considerable portion of the urea‐insoluble proteins and makes them accessible for separation by SDS‐PAGE and LC. The 2‐DE/MS analysis with urea‐solubilized proteins and the 1‐DE‐LC/MS analysis with the urea‐insoluble protein fraction (Pellet) are complementary procedures in the pursuit of a complete proteome analysis. Access to the PROMPT‐generated diagrams in the Proteome Database allows the mining of experimental data with respect to other functional aspects.     

PTM MarkerFinder,a software tool to detect and validate spectra from peptides carrying post‐translational modifications

Mass spectrometry (MS) analysis of peptides carrying post‐translational modifications is challenging due to the instability of some modifications during MS analysis. However, glycopeptides as well as acetylated, methylated and other modified peptides release specific fragment ions during CID (collision‐induced dissociation) and HCD (higher energy collisional dissociation) fragmentation. These fragment ions can be used to validate the presence of the PTM on the peptide. Here, we present PTM MarkerFinder, a software tool that takes advantage of such marker ions. PTM MarkerFinder screens the MS/MS spectra in the output of a database search (i.e., Mascot) for marker ions specific for selected PTMs. Moreover, it reports and annotates the HCD and the corresponding electron transfer dissociation (ETD) spectrum (when present), and summarizes information on the type, number, and ratios of marker ions found in the data set. In the present work, a sample containing enriched N‐acetylhexosamine (HexNAc) glycopeptides from yeast has been analyzed by liquid chromatography‐mass spectrometry on an LTQ Orbitrap Velos using both HCD and ETD fragmentation techniques. The identification result (Mascot .dat file) was submitted as input to PTM MarkerFinder and screened for HexNAc oxonium ions. The software output has been used for high‐throughput validation of the identification results.     

Integrated data management and validation platform for phosphorylated tandem mass spectrometry data

MS/MS is a widely used method for proteome‐wide analysis of protein expression and PTMs. The thousands of MS/MS spectra produced from a single experiment pose a major challenge for downstream analysis. Standard programs, such as MASCOT, provide peptide assignments for many of the spectra, including identification of PTM sites, but these results are plagued by false‐positive identifications. In phosphoproteomic experiments, only a single peptide assignment is typically available to support identification of each phosphorylation site, and hence minimizing false positives is critical. Thus, tedious manual validation is often required to increase confidence in the spectral assignments. We have developed phoMSVal, an open‐source platform for managing MS/MS data and automatically validating identified phosphopeptides. We tested five classification algorithms with 17 extracted features to separate correct peptide assignments from incorrect ones using over 2600 manually curated spectra. The naïve Bayes algorithm was among the best classifiers with an AUC value of 97% and PPV of 97% for phosphotyrosine data. This classifier required only three features to achieve a 76% decrease in false positives as compared with MASCOT while retaining 97% of true positives. This algorithm was able to classify an independent phosphoserine/threonine data set with AUC value of 93% and PPV of 91%, demonstrating the applicability of this method for all types of phospho‐MS/MS data. PhoMSVal is available at http://csbi.ltdk.helsinki.fi/phomsval .     

ICPLQuant – A software for non‐isobaric isotopic labeling proteomics

The main goal of many proteomics experiments is an accurate and rapid quantification and identification of regulated proteins in complex biological samples. The bottleneck in quantitative proteomics remains the availability of efficient software to evaluate and quantify the tremendous amount of mass spectral data acquired during a proteomics project. A new software suite, ICPLQuant, has been developed to accurately quantify isotope‐coded protein label (ICPL)‐labeled peptides on the MS level during LC‐MALDI and peptide mass fingerprint experiments. The tool is able to generate a list of differentially regulated peptide precursors for subsequent MS/MS experiments, minimizing time‐consuming acquisition and interpretation of MS/MS data. ICPLQuant is based on two independent units. Unit 1 performs ICPL multiplex detection and quantification and proposes peptides to be identified by MS/MS. Unit 2 combines MASCOT MS/MS protein identification with the quantitative data and produces a protein/peptide list with all the relevant information accessible for further data mining. The accuracy of quantification, selection of peptides for MS/MS‐identification and the automated output of a protein list of regulated proteins are demonstrated by the comparative analysis of four different mixtures of three proteins (Ovalbumin, Horseradish Peroxidase and Rabbit Albumin) spiked into the complex protein background of the DGPF Proteome Marker.     

Comparative analysis of storage conditions and homogenization methods for tick and flea species for identification by MALDI‐TOF MS

Ticks and fleas are vectors for numerous human and animal pathogens. Controlling them, which is important in combating such diseases, requires accurate identification, to distinguish between vector and non‐vector species. Recently, matrix‐assisted laser desorption/ionization time‐of‐flight mass spectrometry (MALDI‐TOF‐MS) was applied to the rapid identification of arthropods. The growth of this promising tool, however, requires guidelines to be established. To this end, standardization protocols were applied to species of Rhipicephalus sanguineus (Ixodida: Ixodidae) Latreille and Ctenocephalides felis felis (Siphonaptera: Pulicidae) Bouché, including the automation of sample homogenization using two homogenizer devices, and varied sample preservation modes for a period of 1–6 months. The MS spectra were then compared with those obtained from manual pestle grinding, the standard homogenization method. Both automated methods generated intense, reproducible MS spectra from fresh specimens. Frozen storage methods appeared to represent the best preservation mode, for up to 6 months, while storage in ethanol is also possible, with some caveats for tick specimens. Carnoy's buffer, however, was shown to be less compatible with MS analysis for the purpose of identifying ticks or fleas. These standard protocols for MALDI‐TOF MS arthropod identification should be complemented by additional MS spectrum quality controls, to generalize their use in monitoring arthropods of medical interest.     

In planta chemical cross‐linking and mass spectrometry analysis of protein structure and interaction in Arabidopsis

Site‐specific chemical cross‐linking in combination with mass spectrometry analysis has emerged as a powerful proteomic approach for studying the three‐dimensional structure of protein complexes and in mapping protein–protein interactions (PPIs). Building on the success of MS analysis of in vitro cross‐linked proteins, which has been widely used to investigate specific interactions of bait proteins and their targets in various organisms, we report a workflow for in vivo chemical cross‐linking and MS analysis in a multicellular eukaryote. This approach optimizes the in vivo protein cross‐linking conditions in Arabidopsis thaliana, establishes a MudPIT procedure for the enrichment of cross‐linked peptides, and develops an integrated software program, exhaustive cross‐linked peptides identification tool (ECL), to identify the MS spectra of in planta chemical cross‐linked peptides. In total, two pairs of in vivo cross‐linked peptides of high confidence have been identified from two independent biological replicates. This work demarks the beginning of an alternative proteomic approach in the study of in vivo protein tertiary structure and PPIs in multicellular eukaryotes.     

MSDA,a proteomics software suite for in‐depth Mass Spectrometry Data Analysis using grid computing

One of the major bottlenecks in the proteomics field today resides in the computational interpretation of the massive data generated by the latest generation of high‐throughput MS instruments. MS/MS datasets are constantly increasing in size and complexity and it becomes challenging to comprehensively process such huge datasets and afterwards deduce most relevant biological information. The Mass Spectrometry Data Analysis (MSDA, https://msda.unistra.fr ) online software suite provides a series of modules for in‐depth MS/MS data analysis. It includes a custom databases generation toolbox, modules for filtering and extracting high‐quality spectra, for running high‐performance database and de novo searches, and for extracting modified peptides spectra and functional annotations. Additionally, MSDA enables running the most computationally intensive steps, namely database and de novo searches, on a computer grid thus providing a net time gain of up to 99% for data processing.     

Extending the coverage of spectral libraries: A neighbor‐based approach to predicting intensities of peptide fragmentation spectra

Searching spectral libraries in MS/MS is an important new approach to improving the quality of peptide and protein identification. The idea relies on the observation that ion intensities in an MS/MS spectrum of a given peptide are generally reproducible across experiments, and thus, matching between spectra from an experiment and the spectra of previously identified peptides stored in a spectral library can lead to better peptide identification compared to the traditional database search. However, the use of libraries is greatly limited by their coverage of peptide sequences: even for well‐studied organisms a large fraction of peptides have not been previously identified. To address this issue, we propose to expand spectral libraries by predicting the MS/MS spectra of peptides based on the spectra of peptides with similar sequences. We first demonstrate that the intensity patterns of dominant fragment ions between similar peptides tend to be similar. In accordance with this observation, we develop a neighbor‐based approach that first selects peptides that are likely to have spectra similar to the target peptide and then combines their spectra using a weighted K‐nearest neighbor method to accurately predict fragment ion intensities corresponding to the target peptide. This approach has the potential to predict spectra for every peptide in the proteome. When rigorous quality criteria are applied, we estimate that the method increases the coverage of spectral libraries available from the National Institute of Standards and Technology by 20–60%, although the values vary with peptide length and charge state. We find that the overall best search performance is achieved when spectral libraries are supplemented by the high quality predicted spectra.