PhosphoScan: a probability-based method for phosphorylation site prediction using MS2/MS3 pair information

Phosphopeptide identification and phosphorylation site localization are crucial aspects of many biological studies. Furthermore, multiple phosphorylations of peptides make site localization even more difficult. We developed a probability-based method to unambiguously determine phosphorylation sites within phosphopeptides using MS2/3 pair information. A comparison test was performed with SEQUEST and MASCOT predictions using a spectral data set from a synthetic doubly phosphorylated peptide, and the results showed that PhosphoScan analysis yielded a 63% phosphopeptide localization improvement compared with SEQUEST and a 57% improvement compared with MASCOT.     

Confident phosphorylation site localization using the Mascot Delta Score

Large scale phosphorylation analysis is more and more getting into focus of proteomic research. Although it is now possible to identify thousands of phosphorylated peptides in a biological system, confident site localization remains challenging. Here we validate the Mascot Delta Score (MD-score) as a simple method that achieves similar sensitivity and specificity for phosphosite localization as the published Ascore, which is mainly used in conjunction with Sequest. The MD-score was evaluated using liquid chromatography-tandem MS data of 180 individually synthesized phosphopeptides with precisely known phosphorylation sites. We tested the MD-score for a wide range of commonly available fragmentation methods and found it to be applicable throughout with high statistical significance. However, the different fragmentation techniques differ strongly in their ability to localize phosphorylation sites. At 1% false localization rate, the highest number of correctly assigned phosphopeptides was achieved by higher energy collision induced dissociation in combination with an Orbitrap mass analyzer followed very closely by low resolution ion trap spectra obtained after electron transfer dissociation. Both these methods are significantly better than low resolution spectra acquired after collision induced dissociation and multi stage activation. Score thresholds determined from simple calibration functions for each fragmentation method were stable over replicate analyses of the phosphopeptide set. The MD-score outperforms the Ascore for tyrosine phosphorylated peptides and we further show that the ability to call sites correctly increases with increasing distance of two candidate sites within a peptide sequence. The MD-score does not require complex computational steps which makes it attractive in terms of practical utility. We provide all mass spectra and the synthetic peptides to the community so that the development of present and future localization software can be benchmarked and any laboratory can determine MD-scores and localization probabilities for their individual analytical set up.     

Large-scale phosphorylation analysis of alpha-factor-arrested Saccharomyces cerevisiae

Protein phosphorylation is essential for numerous cellular processes. Large-scale profiling of phosphoproteins continues to enhance the depth and speed at which we understand these processes. The development of effective phosphoprotein and peptide enrichment techniques and improvements to mass spectrometric instrumentation have intensified phosphoproteomic research in recent years, leading to unprecedented achievements. Here, we describe a large-scale phosphorylation analysis of alpha-factor-arrested yeast. Using a multidimensional separation strategy involving preparative SDS-PAGE for prefractionation, in-gel digestion with trypsin, and immobilized metal affinity chromatography (IMAC) enrichment of phosphopeptides, followed by LC-MS/MS analysis employing a hybrid LTQ-Orbitrap mass spectrometer, we were able to catalog a substantial portion of the phosphoproteins present in yeast whole-cell lysate. This analysis yielded the confident identification of 2288 nonredundant phosphorylation sites from 985 proteins. The ambiguity score (Ascore) algorithm was utilized to determine the certainty of site localization for the entire data set. In addition, the size of the data set permitted extraction of known and novel kinase motifs using the Motif-X algorithm. Finally, a large number of members of the pheromone signaling pathway were found as phosphoproteins and are discussed.     

Phosphatase-directed phosphorylation-site determination: a synthesis of methods for the detection and identification of phosphopeptides

Phosphopeptides can be difficult to detect and sequence by mass spectrometry (MS) due to low ionization efficiency and suppression effects in the MS mode, and insufficient fragmentation in the tandem MS (MS/MS) mode, respectively. To address this problem, we have developed a technique called Phosphatase-directed Phosphorylation-site Determination (PPD), which combines on-target phosphatase reactions, MALDI MS/MS of IMAC beads on target, and hypothesis-driven MS (HD-MS). In this method, on-target dephosphorylation experiments are conducted on IMAC-bound phosphopeptides, because dephosphorylated peptides have, in general, higher MS sensitivities than the corresponding phosphopeptides. The detected dephosphorylated peptides are sequenced by MS/MS, which identifies the potentially phosphorylated peptide and the total number of Ser, Thr, or Tyr residues that could hypothetically be phosphorylated within that peptide. On the basis of this information, a mass list containing every possible phosphorylation state of each observed peptide (where 1 HPO(3) = 80 Da) is used to direct MALDI-MS/MS on the phosphorylated peptides bound to IMAC beads at each theoretical mass from the list. If the peptide is present, the resulting MS/MS spectrum reveals the exact site(s) of phosphorylation in the peptide. We have demonstrated the applicability of PPD to the detection of in vivo phosphorylation sites on the Drosophila Stem Loop Binding Protein (dSLBP), and the complementarity of this new technique to conventional MS phosphorylation site mapping methods, since the phosphorylation sites in dSLBP could not be detected by other methods.     

Improve the coverage for the analysis of phosphoproteome of HeLa cells by a tandem digestion approach

Complete coverage of all phosphorylation sites in a proteome is the ultimate goal for large-scale phosphoproteome analysis. However, only making use of one protease trypsin for protein digestion cannot cover all phosphorylation sites, because not all tryptic phosphopeptides are detectable in MS. To further increase the phosphoproteomics coverage of HeLa cells, we proposed a tandem digestion approach by using two different proteases. By combining the data set of the first Glu-C digestion and the second trypsin digestion, the tandem digestion approach resulted in the identification of 8062 unique phosphopeptides and 8507 phosphorylation sites in HeLa cells. The conventional trypsin digestion approach resulted in the identification of 3891 unique phosphopeptides and 4647 phosphorylation sites. It was found that the phosphorylation sites identified from the above two approaches were highly complementary. By combining above two data sets, in total we identified 10899 unique phosphopeptides and 11262 phosphorylation sites, corresponding to 3437 unique phosphoproteins with FDR < 1% at peptide level. We also compared the kinase motifs extracted from trypsin, Glu-C, or a second trypsin digestion data sets. It was observed that basophilic motifs were more frequently found in the trypsin and the second trypsin digestion data sets, and the acidic motifs were more frequently found in the Glu-C digestion data set. These results demonstrated that our tandem digestion approach is a good complement to the conventional trypsin digestion approach for improving the phosphoproteomics analysis coverage of HeLa cells.     

Mining phosphopeptide signals in liquid chromatography-mass spectrometry data for protein phosphorylation analysis

Protein phosphorylation is a key post-translational modification that governs biological processes. Despite the fact that a number of analytical strategies have been exploited for the characterization of protein phosphorylation, the identification of protein phosphorylation sites is still challenging. We proposed here an alternative approach to mine phosphopeptide signals generated from a mixture of proteins when liquid chromatography-tandem mass spectrometry (LC-MS/MS) analysis is involved. The approach combined dephosphorylation reaction, accurate mass measurements from a quadrupole/time-of-flight mass spectrometer, and a computing algorithm to differentiate possible phosphopeptide signals obtained from the LC-MS analyses by taking advantage of the mass shift generated by alkaline phosphatase treatment. The retention times and m/z values of these selected LC-MS signals were used to facilitate subsequent LC-MS/MS experiments for phosphorylation site determination. Unlike commonly used neutral loss scan experiments for phosphopeptide detection, this strategy may not bias against tyrosine-phosphorylated peptides. We have demonstrated the applicability of this strategy to sequence more, in comparison with conventional data-dependent LC-MS/MS experiments, phosphopeptides in a mixture of alpha- and beta-caseins. The analytical scheme was applied to characterize the nasopharyngeal carcinoma (NPC) cellular phosphoproteome and yielded 221 distinct phosphorylation sites. Our data presented in this paper demonstrated the merits of computation in mining phosphopeptide signals from a complex mass spectrometric data set.     

LuciPHOr: Algorithm for Phosphorylation Site Localization with False Localization Rate Estimation Using Modified Target-Decoy Approach

The localization of phosphorylation sites in peptide sequences is a challenging problem in large-scale phosphoproteomics analysis. The intense neutral loss peaks and the coexistence of multiple serine/threonine and/or tyrosine residues are limiting factors for objectively scoring site patterns across thousands of peptides. Various computational approaches for phosphorylation site localization have been proposed, including Ascore, Mascot Delta score, and ProteinProspector, yet few address direct estimation of the false localization rate (FLR) in each experiment. Here we propose LuciPHOr, a modified target-decoy-based approach that uses mass accuracy and peak intensities for site localization scoring and FLR estimation. Accurate estimation of the FLR is a difficult task at the individual-site level because the degree of uncertainty in localization varies significantly across different peptides. LuciPHOr carries out simultaneous localization on all candidate sites in each peptide and estimates the FLR based on the target-decoy framework, where decoy phosphopeptides generated by placing artificial phosphorylation(s) on non-candidate residues compete with the non-decoy phosphopeptides. LuciPHOr also reports approximate site-level confidence scores for all candidate sites as a means to localize additional sites from multiphosphorylated peptides in which localization can be partially achieved. Unlike the existing tools, LuciPHOr is compatible with any search engine output processed through the Trans-Proteomic Pipeline. We evaluated the performance of LuciPHOr in terms of the sensitivity and accuracy of FLR estimates using two synthetic phosphopeptide libraries and a phosphoproteomic dataset generated from complex mouse brain samples.Phosphorylation is a common and essential form of post-translational regulation that has been extensively studied via mass spectrometry (1–5). However, tandem mass spectra produced from phosphorylated peptides can be difficult to interpret because of their relatively low abundance within the cell and the presence of intense neutral loss peaks in the MS/MS spectra (6, 7). Correctly determining which residue bears the phosphate group is typically a tedious and error-prone process. Most commonly used database search tools for peptide identification from MS/MS spectra are not optimized for site localization of a post-translational modification, nor do they provide any confidence score for the assigned site. In addition, manual verification of the modification sites is a time-consuming process that requires expertise in mass spectrometry. As a result, the challenges of site localization have been acknowledged by the proteomics community, including within the latest version of the data publication guidelines of this journal (8).A number of computational approaches that localize phosphorylation sites have been reported in the literature, enabling automated phosphoproteomic analysis (reviewed in Ref. 9). These tools either rescore the MS/MS spectra to assign confidence measures for individual sites based on site-determining ions (10–15) or derive localization scores directly from the search engine output (16, 17). Ascore, a representative tool in the rescoring category, scores each candidate phosphosite based upon the peaks representing the site-determining ions and subsequently reports a confidence score for the phosphopeptide sequence (11). This algorithm uses the binomial distribution to compute the probability of a random (incorrect) localization for each candidate site in each spectrum. PhosphoRS extends the scoring approach of Ascore by adjusting the probability of random peak matching based on the density of peaks in different regions of each spectrum (18). In contrast, the Mascot Delta score (MD-score)¹ determines the confidence of phosphosite localization on peptides as the difference in Mascot ion scores between the highest scoring phosphopeptide (the peptide reported by the search engine) and the next best scoring phosphopermutation (same peptide sequence, alternative phosphorylation site (17)). Thus, the MD-score represents the second type of approach, which, instead of rescoring MS/MS spectra for the purpose of improved site localization, derives the scores directly from the database search engine output. A similar idea was implemented in the SLIP score using a modified version of the Batch-Tag search engine of the ProteinProspector suite (16) and in the variable modification localization score of the proprietary software Spectrum Mill (9). These tools, however, apply the logic of delta scoring for individual sites, not for the whole peptide; this is an important consideration in the case of multiply phosphorylated peptides.Although these tools have significantly improved the quality of published phosphopeptide identification data, several important issues remain. The level of uncertainty in modification site localization varies significantly across different peptides depending on the total number of candidate sites and the number of phosphorylated residues on the peptide. This, in turn, makes it difficult to compare localization scores between different peptides. Secondly, few algorithms provide a direct estimation of the false localization rate (FLR) in filtered data. Thirdly, most existing algorithms are tied to specific search engines and/or require proprietary libraries (e.g. Ascore and MD-score were developed for SEQUEST and Mascot, respectively; PhosphoRS requires proprietary libraries from Thermo Scientific). This makes it difficult to access these tools and to compare their performance.Here we present LuciPHOr, an alternative approach for site localization and direct FLR estimation. We introduce a novel scoring approach that utilizes both peak intensity and mass accuracy to aid the computation of an objective score for phosphosite determination and dynamically adapts to characteristic peak properties in different types of instrumentation and fragmentation methods. LuciPHOr computes the scores for phosphosite permutations and associated FLR estimates for the best scoring prediction at the peptide level. It also reports site-level scores for multiphosphorylated peptides, with an acknowledgment that it is difficult to rigorously estimate the FLR in such cases. We also highlight the practical utility of LuciPHOr, which is capable of processing the results of any database search tool (including commonly used search engines X! Tandem (19), SEQUEST (20), and Mascot (21)) that is supported by the widely used Trans-Proteomic Pipeline (TPP) (22). We benchmark LuciPHOr using two previously published datasets generated using synthetic phosphopeptide libraries and demonstrate similar or better performance relative to the existing methods. We also demonstrate the high accuracy of the FLR estimated by LuciPHOr obtained using a target-decoy modification site framework. Lastly, the performance of LuciPHOr is further investigated using a complex mouse brain dataset, and we also discuss the issue of site-level scoring in the analysis of multiphosphorylated peptides.     

Mass spectrometric analysis of the kinetics of in vivo rhodopsin phosphorylation

On stimulation, rhodopsin, the light-sensing protein in the rod cells of the retina, is phosphorylated at several sites on its C terminus as the first step in deactivation. We have developed a mass spectrometry-based method to quantify the kinetics of phosphorylation at each site in vivo. After exposing either a freshly dissected mouse retina or the eye of an anesthetized mouse to a flash of light, phosphorylation and dephosphorylation reactions are terminated by rapidly homogenizing the retina or enucleated eye in 8 M urea. The C-terminal peptide containing all known phosphorylation sites is cleaved from rhodopsin, partially purified by ultracentrifugation, and analyzed by liquid chromatography coupled with mass spectrometry (LCMS). The mass spectrometer responds linearly to the peptide from 10 fmole to 100 pmole. The relative sensitivity to peptides with zero to five phosphates was determined using purified phosphopeptide standards. High pressure liquid chromatography (HPLC) coupled with tandem mass spectrometry (LCMS/MS) was used to distinguish the three primary sites of phosphorylation, Ser 334, Ser 338, and Ser 343. Peptides monophosphorylated on Ser 334 were separable from those monophosphorylated on Ser 338 and Ser 343 by reversed-phase HPLC. Although peptides monophosphorylated at Ser 338 and Ser 343 normally coelute, the relative amounts of each species in the single peak could be determined by monitoring the ratio of specific daughter ions characteristic of each peptide. Doubly phosphorylated rhodopsin peptides with different sites of phosphorylation also were distinguished by LCMS/MS. The sensitivity of these methods was evaluated by using them to measure rhodopsin phosphorylation stimulated either by light flashes or by continuous illumination over a range of intensities.     

Intensity-based protein identification by machine learning from a library of tandem mass spectra

Tandem mass spectrometry (MS/MS) has emerged as a cornerstone of proteomics owing in part to robust spectral interpretation algorithms. Widely used algorithms do not fully exploit the intensity patterns present in mass spectra. Here, we demonstrate that intensity pattern modeling improves peptide and protein identification from MS/MS spectra. We modeled fragment ion intensities using a machine-learning approach that estimates the likelihood of observed intensities given peptide and fragment attributes. From 1,000,000 spectra, we chose 27,000 with high-quality, nonredundant matches as training data. Using the same 27,000 spectra, intensity was similarly modeled with mismatched peptides. We used these two probabilistic models to compute the relative likelihood of an observed spectrum given that a candidate peptide is matched or mismatched. We used a 'decoy' proteome approach to estimate incorrect match frequency, and demonstrated that an intensity-based method reduces peptide identification error by 50-96% without any loss in sensitivity.     

Universal and confident phosphorylation site localization using phosphoRS

An algorithm for the assignment of phosphorylation sites in peptides is described. The program uses tandem mass spectrometry data in conjunction with the respective peptide sequences to calculate site probabilities for all potential phosphorylation sites. Tandem mass spectra from synthetic phosphopeptides were used for optimization of the scoring parameters employing all commonly used fragmentation techniques. Calculation of probabilities was adapted to the different fragmentation methods and to the maximum mass deviation of the analysis. The software includes a novel approach to peak extraction, required for matching experimental data to the theoretical values of all isoforms, by defining individual peak depths for the different regions of the tandem mass spectrum. Mixtures of synthetic phosphopeptides were used to validate the program by calculation of its false localization rate versus site probability cutoff characteristic. Notably, the empirical obtained precision was higher than indicated by the applied probability cutoff. In addition, the performance of the algorithm was compared to existing approaches to site localization such as Ascore. In order to assess the practical applicability of the algorithm to large data sets, phosphopeptides from a biological sample were analyzed, localizing more than 3000 nonredundant phosphorylation sites. Finally, the results obtained for the different fragmentation methods and localization tools were compared and discussed.     

Identification of phosphorylation sites of proteins by high performance liquid chromatography-electrospray ionization-quadrupole ion trap mass spectrometry

The phosphorylation sites of two phosphorylated proteins, bovine β-casein and myelin basic protein (MBP), were identified by high performance liquid chromatography-electrospray ionization-quadrupole ion trap mass spectrometry (HPLC-ESI-QITMS). The tryptic digest of each protein was separated by HPLC, the molecular weight of each peptide was determined by ESI-QITMS on line, and MS/MS spectrum of each peptide was simultaneously obtained by the combination of collision-induced desorption (CID) technique and tandem mass spectrometry (MS/MS) of QITMS. The phosphorylated peptide was identified by looking into whether the difference between the observed and predicted molecular weights of a peptide is 80 u or its integral multiple. Then the phosphorylation site was identified through manual interpretation of the MS/MS spectrum of the phosphorylated peptide or automatic SEQUEST data base-searching.     

Identification of phosphorylation sites of proteins by high performance liquid chromatography-electrospray ionization-quadrupole ion trap mass spectrometry

The phosphorylation sites of two phosphorylated proteins, bovine β-casein and myelin basic protein (MBP), were identified by high performance liquid chromatography-electrospray ionization-quadrupole ion trap mass spectrometry (HPLC-ESI-QITMS). The tryptic digest of each protein was separated by HPLC, the molecular weight of each peptide was determined by ESI-QITMS on line, and MS/MS spectrum of each peptide was simultaneously obtained by the combination of collision-induced desorption (CID) technique and tandem mass spectrometry (MS/MS) of QITMS. The phosphorylated peptide was identified by looking into whether the difference between the observed and predicted molecular weights of a peptide is 80 u or its integral multiple. Then the phosphorylation site was identified through manual interpretation of the MS/MS spectrum of the phosphorylated peptide or automatic SEQUEST data base-searching.     

Toward quantitative phosphotyrosine profiling in vivo

Tyrosine phosphorylation is a dynamic reversible post-translational modification that regulates many aspects of cell biology. To understand how this modification controls biological function, it is necessary to not only identify the specific sites of phosphorylation, but also to quantify how phosphorylation levels on these sites may be altered under specific physiological conditions. Due to its sensitivity and accuracy, mass spectrometry (MS) has widely been applied to the identification and characterization of phosphotyrosine signaling across biological systems. In this review we highlight the advances in both MS and phosphotyrosine enrichment methods that have been developed to enable the identification of low level tyrosine phosphorylation events. Computational and manual approaches to ensure confident identification of phosphopeptide sequence and determination of phosphorylation site localization are discussed along with methods that have been applied to the relative quantification of large numbers of phosphorylation sites. Finally, we provide an overview of the challenges ahead as we extend these technologies to the characterization of tyrosine phosphorylation signaling in vivo. With these latest developments in analytical and computational techniques, it is now possible to derive biological insight from quantitative MS-based analysis of signaling networks in vitro and in vivo. Application of these approaches to a wide variety of biological systems will define how signal transduction regulates cellular physiology in health and disease.     

Time-resolved mass spectrometry of tyrosine phosphorylation sites in the epidermal growth factor receptor signaling network reveals dynamic modules

Ligand binding to cell surface receptors initiates a cascade of signaling events regulated by dynamic phosphorylation events on a multitude of pathway proteins. Quantitative features, including intensity, timing, and duration of phosphorylation of particular residues, may play a role in determining cellular response, but experimental data required for analysis of these features have not previously been available. To understand the dynamic operation of signaling cascades, we have developed a method enabling the simultaneous quantification of tyrosine phosphorylation of specific residues on dozens of key proteins in a time-resolved manner, downstream of epidermal growth factor receptor (EGFR) activation. Tryptic peptides from four different EGFR stimulation time points were labeled with four isoforms of the iTRAQ reagent to enable downstream quantification. After mixing of the labeled samples, tyrosine-phosphorylated peptides were immunoprecipitated with an anti-phosphotyrosine antibody and further enriched by IMAC before LC/MS/MS analysis. Database searching and manual confirmation of peptide phosphorylation site assignments led to the identification of 78 tyrosine phosphorylation sites on 58 proteins from a single analysis. Replicate analyses of a separate biological sample provided both validation of this first data set and identification of 26 additional tyrosine phosphorylation sites and 18 additional proteins. iTRAQ fragment ion ratios provided time course phosphorylation profiles for each site. The data set of quantitative temporal phosphorylation profiles was further characterized by self-organizing maps, which resulted in identification of several cohorts of tyrosine residues exhibiting self-similar temporal phosphorylation profiles, operationally defining dynamic modules in the EGFR signaling network consistent with particular cellular processes. The presence of novel proteins and associated tyrosine phosphorylation sites within these modules indicates additional components of this network and potentially localizes the topological action of these proteins. Additional analysis and modeling of the data generated in this study are likely to yield more sophisticated models of receptor tyrosine kinase-initiated signal transduction, trafficking, and regulation.     

Online automated in vivo zebrafish phosphoproteomics: from large-scale analysis down to a single embryo

In the developing embryo, as in many other biological processes, complex signaling pathways are under tight control of reversible phosphorylation, guiding cell proliferation, differentiation, and growth. Therefore the large-scale identification of signaling proteins and their post-translational modifications is crucial to understand the proteome biology of the developing zebrafish embryo. Here, we used an automated, robust, and sensitive online TiO 2-based LC-MS/MS setup to enrich for phosphorylated peptides from 1 day old zebrafish embryos. We identified, with high confidence, 1067 endogenous phosphorylation sites in a sample taken from 60 embryos (approximately 180 microg), 321 from 10 embryos, and 47 phosphorylation sites from a single embryo, illustrating the sensitivity of the method. This data set, representing by far the largest for zebrafish, was further exploited by searching for serine/threonine or tyrosine kinase motifs using Scansite. For one-third of the identified phosphopeptides a potential kinase motif could be predicted, where it appeared that Cdk5 kinase, p38MAPK, PKA, and Casein Kinase 2 substrates were the most predominant motifs present, underpinning the importance of these kinases in signaling pathways in embryonic development. The phosphopeptide data set was further interrogated using alignments with phosphopeptides identified in recent large-scale phosphoproteomics screens in human and mouse samples. These alignments revealed conservation of phosphorylation sites in several proteins suggesting preserved function in embryonic development.     

Phosphoproteomic analysis of the mouse brain cytosol reveals a predominance of protein phosphorylation in regions of intrinsic sequence disorder

We analyzed the mouse forebrain cytosolic phosphoproteome using sequential (protein and peptide) IMAC purifications, enzymatic dephosphorylation, and targeted tandem mass spectrometry analysis strategies. In total, using complementary phosphoenrichment and LC-MS/MS strategies, 512 phosphorylation sites on 540 non-redundant phosphopeptides from 162 cytosolic phosphoproteins were characterized. Analysis of protein domains and amino acid sequence composition of this data set of cytosolic phosphoproteins revealed that it is significantly enriched in intrinsic sequence disorder, and this enrichment is associated with both cellular location and phosphorylation status. The majority of phosphorylation sites found by MS were located outside of structural protein domains (97%) but were mostly located in regions of intrinsic sequence disorder (86%). 368 phosphorylation sites were located in long regions of disorder (over 40 amino acids long), and 94% of proteins contained at least one such long region of disorder. In addition, we found that 58 phosphorylation sites in this data set occur in 14-3-3 binding consensus motifs, linear motifs that are associated with unstructured regions in proteins. These results demonstrate that in this data set protein phosphorylation is significantly depleted in protein domains and significantly enriched in disordered protein sequences and that enrichment of intrinsic sequence disorder may be a common feature of phosphoproteomes. This supports the hypothesis that disordered regions in proteins allow kinases, phosphatases, and phosphorylation-dependent binding proteins to gain access to target sequences to regulate local protein conformation and activity.     

Reference-facilitated phosphoproteomics: fast and reliable phosphopeptide validation by microLC-ESI-Q-TOF MS/MS

Recent advances in instrument control and enrichment procedures have enabled us to quantify large numbers of phosphoproteins and record site-specific phosphorylation events. An intriguing problem that has arisen with these advances is to accurately validate where phosphorylation events occur, if possible, in an automated manner. The problem is difficult because MS/MS spectra of phosphopeptides are generally more complicated than those of unmodified peptides. For large scale studies, the problem is even more evident because phosphorylation sites are based on single peptide identifications in contrast to protein identifications where at least two peptides from the same protein are required for identification. To address this problem we have developed an integrated strategy that increases the reliability and ease for phosphopeptide validation. We have developed an off-line titanium dioxide (TiO(2)) selective phosphopeptide enrichment procedure for crude cell lysates. Following enrichment, half of the phosphopeptide fractionated sample is enzymatically dephosphorylated, after which both samples are subjected to LC-MS/MS. From the resulting MS/MS analyses, the dephosphorylated peptide is used as a reference spectrum against the original phosphopeptide spectrum, in effect generating two peptide spectra for the same amino acid sequence, thereby enhancing the probability of a correct identification. The integrated procedure is summarized as follows: 1) enrichment for phosphopeptides by TiO(2) chromatography, 2) dephosphorylation of half the sample, 3) LC-MS/MS-based analysis of phosphopeptides and corresponding dephosphorylated peptides, 4) comparison of peptide elution profiles before and after dephosphorylation to confirm phosphorylation, and 5) comparison of MS/MS spectra before and after dephosphorylation to validate the phosphopeptide and its phosphorylation site. This phosphopeptide identification represents a major improvement as compared with identifications based only on single MS/MS spectra and probability-based database searches. We investigated an applicability of this method to crude cell lysates and demonstrate its application on the large scale analysis of phosphorylation sites in differentiating mouse myoblast cells.     

Shotgun cross-linking analysis for studying quaternary and tertiary protein structures

We developed a new approach that employs a novel computer algorithm for the sensitive and high-throughput analysis of tertiary and quaternary interaction sites from chemically cross-linked proteins or multi-protein complexes. First, we directly analyze the digests of the chemically cross-linked proteins using only high-accuracy LC-MS/MS data. We analyze these data using a computer algorithm, we term X!Link, to find cross-links between two peptides. Our algorithm is rapid, taking only a few seconds to analyze approximately 5000 MS/MS spectra. We applied this algorithm to analyze cross-linked sites generated chemically using the amino specific reagent, BS3, in both cytochrome c and the mitochondrial division dynamin mutant, Dnm1G385D, which exists as a stable homodimer. From cytochrome c, a well-established test protein, we identified a total of 31 cross-links, 21 interpeptide and 10 intrapeptide cross-links, in 257 MS/MS spectra from a single LC-MS/MS data set. The high sensitivity of this technique is indicated by the fact that all 19 lysines in cytochrome c were detected as a cross-link product and 33% of all the Lys pairs within 20 A were also observed as a cross-link. Analysis of the cross-linked dimeric form of Dnm1G385D identified a total of 46 cross-links, 38 interpeptide and 8 intrapeptide cross-links, in 98 MS/MS spectra in a single LC-MS/MS data set. These results represent the most abundant cross-links identified in a single protein or protein dimer to date. Statistical analysis suggests a 1% false discovery rate after optimization of filtering parameters. Further analysis of the cross-links identified using our approach indicates that careful manual inspection is important for the correct assignment of cross-linking sites when multiple cross-linkable sites or several similar sequences exist. In summary, we have developed a sensitive MS-based approach to identify peptide-peptide cross-links that does not require isotopic labeling or comparison with non-cross-linked controls, making it faster and simpler than current methodologies.     

Pinpointing phosphorylation sites: Quantitative filtering and a novel site-specific x-ion fragment

Phosphoproteomics deals with the identification and quantification of thousands of phosphopeptides. Localizing the phosphorylation site is however much more difficult than establishing the identity of a phosphorylated peptide. Further, recent findings have raised doubts of the validity of the site assignments in large-scale phosphoproteomics data sets. To improve methods for site localization, we made use of a synthetic phosphopeptide library and SILAC-labeled peptides from whole cell lysates and analyzed these with high-resolution tandem mass spectrometry on an LTQ Orbitrap Velos. We validated gas-phase phosphate rearrangement reactions during collision-induced dissociation (CID) and used these spectra to devise a quantitative filter that by comparing signal intensities of putative phosphorylated fragment ions with their nonphosphorylated counterparts allowed us to accurately pinpoint which fragment ions contain a phosphorylated residue and which ones do not. We also evaluated higher-energy collisional dissociation (HCD) and found this to be an accurate method for correct phosphorylation site localization with no gas-phase rearrangements observed above noise level. Analyzing a large set of HCD spectra of SILAC-labeled phosphopeptides, we identified a novel fragmentation mechanism that generates a phosphorylation site-specific neutral loss derived x-ion, which directly pinpoints the phosphorylated residue. Together, these findings significantly improve phosphorylation site localization confidence.     

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 .