PhoPepMass: A database and search tool assisting human phosphorylation peptide identification from mass spectrometry data

Protein phosphorylation, one of the most important protein post-translational modifications, is involved in various biological processes, and the identification of phosphorylation peptides (phosphopeptides) and their corresponding phosphorylation sites (phosphosites) will facilitate the understanding of the molecular mechanism and function of phosphorylation. Mass spectrometry (MS) provides a high-throughput technology that enables the identification of large numbers of phosphosites. PhoPepMass is designed to assist human phosphopeptide identification from MS data based on a specific database of phophopeptide masses and a multivariate hypergeometric matching algorithm. It contains 244,915 phosphosites from several public sources. Moreover, the accurate masses of peptides and fragments with phosphosites were calculated. It is the first database that provides a systematic resource for the query of phosphosites on peptides and their corresponding masses. This allows researchers to search certain proteins of which phosphosites have been reported, to browse detailed phosphopeptide and fragment information, to match masses from MS analyses with defined threshold to the corresponding phosphopeptide, and to compare proprietary phosphopeptide discovery results with results from previous studies. Additionally, a database search software is created and a “two-stage search strategy” is suggested to identify phosphopeptides from tandem mass spectra of proteomics data. We expect PhoPepMass to be a useful tool and a source of reference for proteomics researchers. PhoPepMass is available at https://www.scbit.org/phopepmass/index.html.     

Improved titanium dioxide enrichment of phosphopeptides from HeLa cells and high confident phosphopeptide identification by cross-validation of MS/MS and MS/MS/MS spectra

Enrichment is essential for phosphoproteome analysis because phosphorylated proteins are usually present in cells in low abundance. Recently, titanium dioxide (TiO2) has been demonstrated to enrich phosphopeptides from simple peptide mixtures with high specificity; however, the technology has not been optimized. In the present study, significant non-specific bindings were observed when proteome samples were applied to TiO2 columns. Column wash with an NH4Glu solution after loading peptide mixtures significantly increased the efficiency of TiO2 phosphopeptide enrichment with a recovery of up to 84%. Also, for proteome samples, more than a 2-fold increase in unique phosphopeptide identifications has been achieved. The use of NH4Glu for a TiO2 column wash does not significantly reduce the phosphopeptide recovery. A total of 858 phosphopeptides corresponding to 1034 distinct phosphosites has been identified from HeLa cells using the improved TiO2 enrichment procedure in combination with data-dependent neutral loss nano-RPLC-MS2-MS3 analysis. While 41 and 35% of the phosphopeptides were identified only by MS2 and MS3, respectively, 24% was identified by both MS2 and MS3. Cross-validation of the phosphopeptide assignment by MS2 and MS3 scans resulted in the highest confidence in identification (99.5%). Many phosphosites identified in this study appear to be novel, including sites from antigen Ki-67, nucleolar phosphoprotein p130, and Treacle protein. The study also indicates that evaluation of confidence levels for phosphopeptide identification via the reversed sequence database searching strategy might underestimate the false positive rate.     

Characterization of a TiO₂ enrichment method for label-free quantitative phosphoproteomics

Phosphorylation is a protein post-translational modification with key roles in the regulation of cell biochemistry and signaling. In-depth analysis of phosphorylation using mass spectrometry is permitting the investigation of processes controlled by phosphorylation at the system level. A critical step of these phosphoproteomics methods involves the isolation of phosphorylated peptides from the more abundant unmodified peptides produced by the digestion of cell lysates. Although different techniques to enrich for phosphopeptides have been reported, there are limited data on their suitability for direct quantitative analysis by MS. Here we report a TiO₂ based enrichment method compatible with large-scale and label-free quantitative analysis by LC–MS/MS. Starting with just 500 μg of protein, the technique reproducibly isolated hundreds of peptides, >85% of which were phosphorylated. These results were obtained by using relatively short LC–MS/MS gradient runs (45 min) and without any previous separation step. In order to characterize the performance of the method for quantitative analyses, we employed label-free LC–MS/MS using extracted ion chromatograms as the quantitative readout. After normalization, phosphopeptides were quantified with good precision (coefficient of variation was 20% on average, n = 900 phosphopeptides), linearity (correlation coefficients >0.98) and accuracy (deviations <20%). Thus, phosphopeptide ion signals correlated with the concentration of the respective phosphopeptide in samples, making the approach suitable for in-depth relative quantification of phosphorylation by label-free LC–MS/MS.     

Development of immobilized Sn4+ affinity chromatography material for highly selective enrichment of phosphopeptides

In this work, we first immobilized tin(IV) ion on polydopamine‐coated magnetic graphene (magG@PDA) to synthesize Sn⁴⁺‐immobilized magG@PDA (magG@PDA‐Sn⁴⁺) and successfully applied the material to highly selective enrichment of phosphopeptides. The material gathered the advantages of large surface area of graphene, superparamagnetism of Fe₃O₄, good hydrophilicity and biocompatibility of polydopamine, and strong interaction between Sn⁴⁺ and phosphopeptides. The enrichment performance of magG@PDA‐Sn⁴⁺ toward phosphopeptides from digested β‐casein at different concentrations, with and without added digested BSA was investigated and compared with magG@PDA‐Ti⁴⁺. The results showed high selectivity and sensitivity of the Sn⁴⁺‐IMAC material toward phosphopeptides, as good as the Ti⁴⁺‐IMAC material. Finally, magG@PDA‐Sn⁴⁺ was applied to the analysis of endogenous phosphopeptides from a real sample, human saliva, with both MALDI‐TOF MS and nano‐LC‐ESI‐MS/MS. The results indicated that the as‐synthesized Sn⁴⁺‐IMAC material not only has good enrichment performance, but also could serve as a supplement to the Ti⁴⁺‐IMAC material and expand the phosphopeptide coverage enriched by the single Ti⁴⁺‐IMAC material, demonstrating the broad application prospects of magG@PDA‐Sn⁴⁺ in phosphoproteome research.     

Importance of Manual Validation for the Identification of Phosphopeptides Using a Linear Ion Trap Mass Spectrometer

Accurate determination of protein phosphorylation is challenging, particularly for researchers who lack access to a high-accuracy mass spectrometer. In this study, multiple protocols were used to enrich phosphopeptides, and a rigorous filtering workflow was used to analyze the resulting samples. Phosphopeptides were enriched from cultured rat renal proximal tubule cells using three commonly used protocols and a dual method that combines separate immobilized metal affinity chromatography (IMAC) and titanium dioxide (TiO₂) chromatography, termed dual IMAC (DIMAC). Phosphopeptides from all four enrichment strategies were analyzed by liquid chromatography-multiple levels of mass spectrometry (LC-MSⁿ) neutral-loss scanning using a linear ion trap mass spectrometer. Initially, the resulting MS² and MS³ spectra were analyzed using PeptideProphet and database search engine thresholds that produced a false discovery rate (FDR) of <1.5% when searched against a reverse database. However, only 40% of the potential phosphopeptides were confirmed by manual validation. The combined analyses yielded 110 confidently identified phosphopeptides. Using less-stringent initial filtering thresholds (FDR of 7–9%), followed by rigorous manual validation, 262 unique phosphopeptides, including 111 novel phosphorylation sites, were identified confidently. Thus, traditional methods of data filtering within widely accepted FDRs were inadequate for the analysis of low-resolution phosphopeptide spectra. However, the combination of a streamlined front-end enrichment strategy and rigorous manual spectral validation allowed for confident phosphopeptide identifications from a complex sample using a low-resolution ion trap mass spectrometer.     

Identification of phosphopeptides by MALDI Q-TOF MS in positive and negative ion modes after methyl esterification

We have developed an efficient, sensitive, and specific method for the detection of phosphopeptides present in peptide mixtures by MALDI Q-TOF mass spectrometry. Use of the MALDI Q-TOF enables selection of phosphopeptides and characterization by CID of the phosphopeptides performed on the same sample spot. However, this type of experiment has been limited by low ionization efficiency of phosphopeptides in positive ion mode while selecting precursor ions of phosphopeptides. Our method entails neutralizing negative charges on acidic groups of nonphosphorylated peptides by methyl esterification before mass spectrometry in positive and negative ion modes. Methyl esterification significantly increases the relative signal intensity generated by phosphopeptides in negative ion mode compared with positive ion mode and greatly increases selectivity for phosphopeptides by suppressing the signal intensity generated by acidic peptides in negative ion mode. We used the method to identify 12 phosphopeptides containing 22 phosphorylation sites from low femtomolar amounts of a tryptic digest of beta-casein and alpha-s-casein. We also identified 10 phosphopeptides containing five phosphorylation sites from an in-gel tryptic digest of 100 fmol of an in vitro autophosphorylated fibroblast growth factor receptor kinase domain and an additional phosphopeptide containing another phosphorylation site when 500 fmol of the digest was examined. The results demonstrate that the method is a fast, robust, and sensitive means of characterizing phosphopeptides present in low abundance mixtures of phosphorylated and nonphosphorylated peptides.     

Carboxy group derivatization for enhanced electron‐transfer dissociation mass spectrometric analysis of phosphopeptides

A novel strategy based on carboxy group derivatization is presented for specific characterization of phosphopeptides. By tagging the carboxy group with 1‐(2‐pyrimidyl) piperazine (PP), the ion charge states of phosphopeptides can be largely enhanced, showing great advantages for sequencing phosphorylated peptides with electron‐transfer dissociation MS. Besides, after PP‐derivatization, most non‐specific bindings can be avoided by eliminating the interaction between the carboxy group and TiO₂, greatly improving the specificity of TiO₂‐based phosphopeptide enrichment strategy. Moreover, being tagged with a hydrophobic group, the retention time of phosphopeptides in RPLC can be prolonged, overcoming the difficulty of separating phosphopeptides in RPLC‐based approach. Together with several other advantages, such as ease of handling, rapid reaction time, broad applicability and good reproducibility, this PP‐derivatization method is promising for high‐throughput phosphoproteome research.     

Efficient enrichment of phosphopeptides by magnetic TiO₂-coated carbon-encapsulated iron nanoparticles

Titanium dioxide (TiO₂) has been widely used for phosphopeptide enrichment. Several approaches have been reported to produce magnetic TiO₂ affinity probes. In this report, we present a facile approach to immobilize TiO₂ onto poly(acrylic acid)‐functionalized magnetic carbon‐encapsulated iron nanoparticles as affinity probes for efficient enrichment of phosphopeptides. By using the new magnetic TiO₂ affinity probes, denoted as TiO₂‐coated Fe@CNPs, rapid and effective MALDI‐TOF MS profiling of phosphopeptides was demonstrated in different model systems such as tryptic digests of β‐casein, and complex β‐casein/BSA mixture. The TiO₂‐coated Fe@CNPs out‐performed the commercial TiO₂‐coated magnetic beads for detection of phosphopeptides from tryptic digests of β‐casein/BSA mixture with a molar ratio of 1:100. The new TiO₂‐coated magnetic probes were also proven to be applicable for real life samples. The magnetic TiO₂‐coated Fe@CNPs were employed to selectively isolate phosphopeptides from tryptic digests of HeLa cell lysates and out‐performed the commercial magnetic TiO₂ beads in the number of identified phosphopeptides and phosphorylation sites. In a 200‐μg equivalent of HeLa cell lysates, we identified 1415 unique phosphopeptides and 1093 phosphorylation sites, indicating the good performance of the new approach.     

The Global Phosphoproteome of Chlamydomonas reinhardtii Reveals Complex Organellar Phosphorylation in the Flagella and Thylakoid Membrane

Chlamydomonas reinhardtii is the most intensively-studied and well-developed model for investigation of a wide-range of microalgal processes ranging from basic development through understanding triacylglycerol production. Although proteomic technologies permit interrogation of these processes at the protein level and efforts to date indicate phosphorylation-based regulation of proteins in C. reinhardtii is essential for its underlying biology, characterization of the C. reinhardtii phosphoproteome has been limited. Herein, we report the richest exploration of the C. reinhardtii proteome to date. Complementary enrichment strategies were used to detect 4588 phosphoproteins distributed among every cellular component in C. reinhardtii. Additionally, we report 18,160 unique phosphopeptides at <1% false discovery rate, which comprise 15,862 unique phosphosites - 98% of which are novel. Given that an estimated 30% of proteins in a eukaryotic cell are subject to phosphorylation, we report the majority of the phosphoproteome (23%) of C. reinhardtii. Proteins in key biological pathways were phosphorylated, including photosynthesis, pigment production, carbon assimilation, glycolysis, and protein and carbohydrate metabolism, and it is noteworthy that hyperphosphorylation was observed in flagellar proteins. This rich data set is available via ProteomeXchange (ID: PXD000783) and will significantly enhance understanding of a range of regulatory mechanisms controlling a variety of cellular process and will serve as a critical resource for the microalgal community.Chlamydomonas reinhardtii (C. reinhardtii)¹ is the most intensively studied and well-developed microalgal model species for investigation of a wide-range of processes ranging from basic development through understanding triacylglycerol production. C. reinhardtii is easy to culture, grows quickly, and is tolerant to varying growth conditions. Additionally, the genome of C. reinhardtii is sequenced (1) and C. reinhardtii is easily engineered at the genetic level (2), thus making it an attractive model system for investigation of a wide range of underlying biology processes, including photosynthesis, cell motility, and phototaxis, cell-wall biogenesis, and other fundamental cellular processes (3).Advances in proteomic technologies permit ever increasing breadth and depth for interrogation of protein level dynamics, and the definitive role of phosphorylation in affecting a protein''s function, activity, localization, stability, and ligand/protein interactions is well understood (4). However, compared with Arabidopsis and other plant species (5), the C. reinhardtii phosphoproteome data set is still in nascent assembly. In a series of studies, researchers investigated the effects of environmental changes on 43 phosphopeptides among thylakoid membrane-associated proteins (6–8), analysis of which provides evidence for a thylakoid protein kinase cascade. Wagner et al. (9) observed 83 phosphopeptides associated with the eyespot apparatus, including several kinases and phosphatases implicated in phosphorylation-based signaling in the eyespot. In a study of C. reinhardtii flagella, Pan et al. (10) observed 1296 spectral counts of phosphopeptides corresponding to 224 phosphoproteins involved with motility and assembly. In a similar study, Boesger et al. (11) observed 141 phosphopeptides corresponding to 32 proteins. Using whole cells, Wagner et al. (12) observed 360 phosphopeptides corresponding to 328 proteins, including several flagellar kinases, which indicates the importance of phosphorylation-based signaling for motility and assembly.Despite the importance of phosphorylation-based signaling underlying C. reinhardtii biological processes, characterization of the cellular pool of phosphopeptides has been limited. Although additional dimensions of separation that are orthogonal to online reversed-phase are routinely used in order to probe phosphopeptide species of low-abundance, this has not been implemented for probing the C. reinhardtii phosphoproteome. Hydrophilic-interaction liquid chromatography improves phosphopeptide separation and detection (13) and is more orthogonal than strong-cation exchange compared with online reversed-phase chromatography (14). Additionally, to complement the increased resolution of phosphopeptides afforded by a first-dimension separation, enrichment strategies based on the affinity of a phosphate group to a metal ion or metal oxide can further increase coverage. Currently, a single immobilized metal affinity chromatography (IMAC) scheme is the most popular choice for phosphopeptide studies using C. reinhardtii. However, conventional insoluble TiO₂ beads recover more phosphopeptides than traditional IMAC (15). Additionally, PolyMAC (polymer-based metal ion affinity capture) is a polymer-based improved analog of IMAC that uses TiO₂-functionalized soluble nanopolymers to chelate phosphopeptides in a homogeneous aqueous environment (15). Thus, use of complementary enrichment schemes based on TiO₂ and PolyMAC can yield more comprehensive results compared with a single strategy.In this study, complementary approaches using TiO₂/PolyMAC enrichment and hydrophilic-interaction liquid chromatography (HILIC) chromatography were employed to explore the C. reinhardtii phosphoproteome in significant depth. We report the detection of 4588 nonredundant phosphoproteins from 18,160 unique phosphopeptides at <1% false discovery rate. Among these peptides, we report 15,862 unique phosphosites identified with ≥95% localization probability. Nearly all reported sites are novel. Our data show many key biological pathways, including photosynthesis, chlorophyll biosynthesis, carbon assimilation, protein metabolism, and flagella assembly and motility are comprised of multiple phosphoproteins. These data provide a framework for garnering novel mechanistic insights into understanding a variety of cellular/signaling processes.     

Colander: a probability-based support vector machine algorithm for automatic screening for CID spectra of phosphopeptides prior to database search

We developed a probability-based machine-learning program, Colander, to identify tandem mass spectra that are highly likely to represent phosphopeptides prior to database search. We identified statistically significant diagnostic features of phosphopeptide tandem mass spectra based on ion trap CID MS/MS experiments. Statistics for the features are calculated from 376 validated phosphopeptide spectra and 376 nonphosphopeptide spectra. A probability-based support vector machine (SVM) program, Colander, was then trained on five selected features. Data sets were assembled both from LC/LC-MS/MS analyses of large-scale phosphopeptide enrichments from proteolyzed cells, tissues and synthetic phosphopeptides. These data sets were used to evaluate the capability of Colander to select pS/pT-containing phosphopeptide tandem mass spectra. When applied to unknown tandem mass spectra, Colander can routinely remove 80% of tandem mass spectra while retaining 95% of phosphopeptide tandem mass spectra. The program significantly reduced computational time spent on database search by 60-90%. Furthermore, prefiltering tandem mass spectra representing phosphopeptides can increase the number of phosphopeptide identifications under a predefined false positive rate.     

Automated,Reproducible, Titania-Based Phosphopeptide Enrichment Strategy for Label-Free Quantitative Phosphoproteomics

An automated phosphopeptide enrichment strategy is described using titanium dioxide (TiO₂)-packed, fused silica capillaries for use with liquid chromatography (LC)-mass spectrometry (MS)/MS-based, label-free proteomics workflows. To correlate an optimum peptide:TiO₂ loading ratio between different particle types, the ratio of phenyl phosphate-binding capacities was used. The optimum loading for the column was then verified through replicate enrichments of a range of quantities of digested rat brain tissue cell lysate. Fractions were taken during sample loading, multiple wash steps, and the elution steps and analyzed by LC-MS/MS to gauge the efficiency and reproducibility of the enrichment. Greater than 96% of the total phosphopeptides were detected in the elution fractions, indicating efficient trapping of the phosphopeptides on the first pass of enrichment. The quantitative reproducibility of the automated setup was also improved greatly with phosphopeptide intensities from replicate enrichments exhibiting a median coefficient of variation (CV) of 5.8%, and 80% of the identified phosphopeptides had CVs below 11.1%, while maintaining >85% specificity. By providing this high degree of analytical reproducibility, this method allows for label-free phosphoproteomics over large sample sets with complex experimental designs (multiple biological conditions, multiple biological replicates, multiple time-points, etc.), including large-scale clinical cohorts.     

Protein kinase A phosphorylation characterized by tandem Fourier transform ion cyclotron resonance mass spectrometry

A microelectrospray ionization tandem Fourier transform ion cyclotron resonance mass spectrometry (ESI FT-ICR MS(n)) approach for structural characterization of protein phosphorylation is described. Identification of proteolytic peptides is based solely upon mass measurement by high field (9.4 Tesla) FT-ICR MS. The location of the modification within any phosphopeptide is then established by FT-ICR MS(2) and MS(3) experiments. Structural information is maximized by use of electron capture dissociation (ECD) and/or infrared multiphoton dissociation (IRMPD). The analytical utility of the method is demonstrated by characterization of protein kinase A (PKA) phosphorylation. In a single FT-ICR MS experiment, 30 PKA tryptic peptides (including three phosphopeptides) were mass measured by internal calibration to within an absolute mean error of |0.7 ppm|. The location of each of the three sites of phosphorylation was then determined by MS(2) and MS(3) experiments, in which ECD and IRMPD provide complementary peptide sequence information. In two out of three cases, electron irradiation of a phosphopeptide [M + nH](n+) ion produced an abundant charge-reduced [M + nH]((n-1)+*) ion, but few sequence-specific c and z(*) fragment ions. Subsequent IRMPD (MS(3)) of the charge-reduced radical ion resulted in the detection of a large number of ECD-type ion products (c and z ions), but no b or y type ions. The utility of activated ion ECD for the characterization of tryptic phosphopeptides was then demonstrated.     

Nanoprobe-based immobilized metal affinity chromatography for sensitive and complementary enrichment of multiply phosphorylated peptides

Magnetic nanoparticles (MNP, <100 nm) have rapidly evolved as sensitive affinity probes for phosphopeptide enrichment. By taking advantage of the easy magnetic separation and flexible surface modification of the MNP, we developed a surface‐blocked, nanoprobe‐based immobilized metal ion affinity chromatography (NB‐IMAC) method for the enhanced purification of multiply phosphorylated peptides. The NB‐IMAC method allowed rapid and specific one‐step enrichment by blocking the surface of titanium (IV) ion‐charged nitrilotriacetic acid‐conjugated MNP (Ti⁴⁺‐NTA‐PEG@MNP) with low molecular weight polyethylene glycol. The MNP demonstrated highly sensitive and unbiased extraction of both mono‐ and multiply phosphorylated peptides from diluted β‐casein (2×10^?10 M). Without chemical derivation or fractionation, 1283 phosphopeptides were identified from 400 μg of Raji B cells with 80% purification specificity. We also showed the first systematic comparison on the particle size effect between nano‐sclae IMAC and micro‐scale IMAC. Inductively coupled plasma‐mass spectrometry (ICP‐MS) analysis revealed that MNP had a 4.6‐fold higher capacity for metal ions per unit weight than did the magnetic micro‐sized particle (MMP, 2–10 μm), resulting in the identification of more phosphopeptides as well as a higher percentage of multiply phosphorylated peptides (31%) at the proteome scale. Furthermore, NB‐IMAC complements chromatography‐based IMAC and TiO₂ methods because <13% of mono‐ and 12% of multiply phosphorylated peptide identifications overlapped among the 2700 phosphopeptides identified by the three methods. Notably, the number of multiply phosphorylated peptides was enriched twofold and threefold by NB‐IMAC relative to micro‐scale IMAC and TiO₂, respectively. NB‐IMAC is an innovative material for increasing the identification coverage in phosphoproteomics.     

Neutron-encoded Signatures Enable Product Ion Annotation From Tandem Mass Spectra

We report the use of neutron-encoded (NeuCode) stable isotope labeling of amino acids in cell culture for the purpose of C-terminal product ion annotation. Two NeuCode labeling isotopologues of lysine, ¹³C₆¹⁵N₂ and ²H₈, which differ by 36 mDa, were metabolically embedded in a sample proteome, and the resultant labeled proteins were combined, digested, and analyzed via liquid chromatography and mass spectrometry. With MS/MS scan resolving powers of ∼50,000 or higher, product ions containing the C terminus (i.e. lysine) appear as a doublet spaced by exactly 36 mDa, whereas N-terminal fragments exist as a single m/z peak. Through theory and experiment, we demonstrate that over 90% of all y-type product ions have detectable doublets. We report on an algorithm that can extract these neutron signatures with high sensitivity and specificity. In other words, of 15,503 y-type product ion peaks, the y-type ion identification algorithm correctly identified 14,552 (93.2%) based on detection of the NeuCode doublet; 6.8% were misclassified (i.e. other ion types that were assigned as y-type products). Searching NeuCode labeled yeast with PepNovo⁺ resulted in a 34% increase in correct de novo identifications relative to searching through MS/MS only. We use this tool to simplify spectra prior to database searching, to sort unmatched tandem mass spectra for spectral richness, for correlation of co-fragmented ions to their parent precursor, and for de novo sequence identification.The ability to make de novo sequence identifications directly from tandem mass spectra has long been a holy grail of the proteomic community. Such a capability would wean the field from its reliance upon sequenced genome databases. Even for organisms with fully annotated genomes, events such as single nucleotide polymorphisms, alternative splicing, gene fusion, and a host of other genomic transformations can result in altered proteomes. These alterations can vary from cell to cell and individual to individual. Thus, one could argue that the most valuable proteomic information, the individual and cellular proteome variation from the genome, remains elusive (1). This problem has received considerable attention; that said, it is not easy to de novo correlate spectrum to sequence in a large-scale, automated fashion (2–6). Improvements in mass accuracy have helped, but routine, reliable de novo sequencing without database assistance is not standard (7–10).A primary means to facilitate de novo spectral interpretation is the simple annotation of m/z peaks in tandem mass spectra as either N- or C-terminal. We and others have investigated this seemingly simple first step. Real-world spectra, however, are complex. Difficulties often arise in determining the charge state of the fragment or in differentiating between fragment ions and peaks arising from neutral loss, internal fragmentation, or spectral noise, both electronic and chemical. Several strategies have focused on product ion annotation. These approaches have included manipulation of the N-terminus basicity combined with electron transfer dissociation (ETD)¹ (11–13). This approach can yield mostly N-terminal fragments for peptides having only two charges. However, it requires both ETD and the protease LysN. Other methods have used differential labeling of N- and C-terminal peptides to shift either one or the other product ion series, by either metabolic or chemical means (14–18). Metabolic incorporation of amino acids is an efficient method of introducing distinctive labels that eliminates in vitro labeling, but this method requires that the sample be amenable to cell culture (19, 20). Additionally, it may be difficult to achieve complete labeling in complex systems. Several other approaches used to introduce heavy isotopes onto one terminus have been investigated, including trypsin digestion in ¹⁸O water (21–23), differential isotopic esterification (24, 25), derivatization of the C-terminal carboxylate by p-bromophenethylamine (8, 26), N-terminal derivatization with sulfonic acid groups (27, 28), and formaldehyde labeling via reductive amination (29–31). These chemical modifications are introduced after cell lysis, often immediately prior to analysis. Although chemical labeling strategies can be used with a variety of samples, difficulties can arise from differences in labeling efficiency between samples, and often a clean-up step is required following labeling, which may lead to sample loss. No matter the labeling method, in this regime, the two precursors must be separately isolated, fragmented, and analyzed either together or separately. The recognition and selection of the broadly spaced doublet in real time also are necessary. These requirements have limited the utility of these approaches. Our own laboratory discovered that the c- and ^●z-type product ions generated from either electron capture dissociation or ETD have distinct chemical formulae and therefore can always be distinguished based on accurate mass alone (32). The problem with this approach is that extremely high mass accuracy (<500 ppb) is required in order to distinguish these product ion types above ∼600 Da in mass. Thus, the majority of the product ions within a spectrum cannot be readily mapped to either terminus with high confidence.Despite these difficulties, we assert that robust de novo sequencing methodology would benefit greatly from a simple method that could be used to distinguish N- and C-terminal product ions with high accuracy and precision. Ideally, the approach would work regardless of the choice of proteolytic enzyme or dissociation method. Recently, we described a new technology for protein quantification called neutron encoding (NeuCode) (33). NeuCode embeds millidalton mass differences into peptides and proteins by exploiting the mass defect induced by differences in the nuclear binding energies of the various stable isotopes of common elements such as C, N, H, and O. For example, consider the amino acid lysine, which has eight additional neutrons (+8 Da). One way to synthesize this amino acid is to add six ¹³C atoms and two ¹⁵N atoms (+8.0142 Da). Another isotopologue could be constructed by adding eight ²H atoms (+8.0502). These two isotopologues differ by only 36 mDa; peptide precursors containing both of these amino acids would appear as a single, unresolved precursor m/z peak at a mass resolving power of less than ∼100,000. However, under high resolving powers (i.e. greater than ∼100,000 at m/z 400), this doublet is resolved. We first developed this NeuCode concept in the context of metabolic labeling, akin to stable isotope labeling with amino acids in cell culture (SILAC), except that instead of the precursor partners being separated by 4 to 8 Da, they are separated by only 6 to 40 mDa. For quantitative purposes, NeuCode promises to deliver ultraplexed SILAC (>12) without increasing spectral complexity.We reasoned that the isotopologues of Lys that permit NeuCode SILAC would generate a distinct fingerprint on C-terminal product ions. Specifically, peptides that have been labeled with NeuCode SILAC and digested with LysC uniformly contain Lys at the C terminus. Upon MS/MS, all C-terminal product ions should present as doublets (with duplex NeuCode), whereas N-terminal products will be detected as a single m/z peak. The very close m/z spacing of the NeuCode SILAC partners will ensure that each partner is always co-isolated and that the signatures are visible only upon high-resolving-power mass analysis. Here we investigate the combination of NeuCode SILAC and high-resolving-power MS/MS analysis to allow the straightforward identification of C-terminal product ions.

Sample Preparation

Saccharomyces cerevisiae strain BY4741 Lys1Δ was grown in defined synthetic complete (SC, Sunrise Science, San Diego, CA) drop-out media with either heavy 6C¹³/2N¹⁵ lysine (+8.0142 Da, Cambridge Isotopes, Tewksbury, MA), or heavy 8D (+8.0502 Da, Cambridge Isotopes). Cells were propagated to a minimum of 10 doublings. At mid-log phase, cells were harvested via centrifugation at 3,000 × g for 3 min and then washed three times with chilled double distilled H₂O. Cell pellets were resuspended in 5 ml lysis buffer (50 mm Tris pH 8, 8 m urea, 75 mm sodium chloride, 100 mm sodium butyrate, 1 mm sodium orthovanadate, protease and phosphatase inhibitor tablet), and protein was extracted via glass bead milling (Retsch, Haan, Germany). Protein concentration was measured via BCA (Pierce). Cysteines in the yeast lysate were reduced with 5 m dithiothreitol at ambient temperature for 30 min, alkylated with 15 mm iodoacetamide in the dark at ambient temperature for 30 min, and then quenched with 5 mm dithiothreitol. 50 mm tris (pH 8.0) was used to dilute the urea concentration to 4 m. Proteins were digested with LysC (1:50 enzyme:protein ratio) at ambient temperature for 16 h. The digestion was quenched with TFA and desalted with a tC18 Sep-Pak (Waters, Etten-Leur, The Netherlands). Samples were prepared by mixing 6C¹³/2N¹⁵ (+8.0412 Da) and 8D (+8.0502 Da) labeled peptides in 1:1 ratios by mass. For strong cation exchange fractionation, peptides were dissolved in 400 μl of strong cation exchange buffer A (5 mm KH₂PO₄ and 30% acetonitrile; pH 2.65) and injected onto a polysulfoethylaspartamide column (9.4 mm × 200 mm; PolyLC) attached to a Surveyor LC quarternary pump (Thermo Electron, West Chester, PA) operating at 3 ml/min. Peptides were detected by photodiode array detector (Thermo Electron, West Chester, PA). Fractions were collected every 2 min starting at 10 min into the following gradient: 0–2 min at 100% buffer A, 2–5 min at 0%–15% buffer B (5 mm KH₂PO₄, 30% acetonitrile, and 350 mm KCl (pH 2.65)), and 5–35 min at 15%–100% buffer B. Buffer B was held at 100% for 10 min. Finally, the column was washed with buffer C (50 mm KH₂PO₄ and 500 mm KCl (pH 7.5)) and water before recalibration. Fractions were collected by hand every 2 to 3 min starting at 10 min into the gradient and were lyophilized and desalted with a tC18 Sep-Pak (Waters).

LC-MS/MS

Samples were loaded onto a 15-cm-long, 75-μm capillary column packed with 5 μm Magic C18 (Michrom, Auburn, CA) particles in mobile phase A (0.2% formic acid in water). Peptides were eluted with mobile phase B (0.2% formic acid in acetonitrile) over a 120-min gradient at a flow rate of 300 nl/min. Eluted peptides were analyzed by an Orbitrap Elite mass spectrometer. For the nonfractionated samples, mass spectrometer instrument methods comprised one MS¹ scan followed by data-dependent MS² scans of the five most intense precursors. A survey MS¹ scan was performed by the Orbitrap at 30,000 resolving power to identify precursors to sample for tandem mass spectrometry, and this was followed by an additional MS¹ scan at 480,000 resolving power (at m/z 400; actual mass resolving power of 470,700). Data-dependent tandem mass spectrometry was performed via beam-type collisional activated dissociation (HCD) in the Orbitrap at a resolving power of 15,000, 60,000, 120,000, or 240,000 and a collision energy of 30. Preview mode was enabled, and precursors of unknown charge or with a charge of +1 were excluded from MS² sampling. For experiments comparing the duty cycle and resolving power required in order to distinguish y-ion doublets, MS¹ and MS² target ion accumulation values were set to 5 × 10⁵ and 5 × 10⁴, respectively. For all other experiments, MS¹ target accumulation values were set to 1 × 10⁶ and MS² accumulation values were set to 4 × 10⁵. Dynamic exclusion was set to 30 s for −0.55 m/z and +2.55 m/z of selected precursors. For ETD analysis, data-dependent top-five mass spectrometry was performed at a resolving power of 240,000 (m/z 400; actual MS² mass resolving power of 271,000) (34). ETD accumulation values were set to 1 × 10⁶ for MS¹ target accumulation and 4 × 10⁵ for MS² target accumulation. The fluoranthene reaction time was set to 100 ms. For the high-pH strong cation exchange fractions, data-dependent tandem mass spectrometry was performed via HCD at a resolving power of either 60,000 or 120,000 and a collision energy of 30. Preview mode was enabled, and precursors of unknown charge or with a charge of +1 were excluded from MS² sampling. MS¹ targets were set to 1 × 10⁶, and MS² accumulation values were set to 4 × 10⁵. Dynamic exclusion was set to 45 s for −0.55 m/z and +2.55 m/z of selected precursors. Analysis by use of a wide isolation window was performed on an Orbitrap Fusion. MS¹ analysis was performed at 450,000 resolving power (m/z 200), and MS² analysis was performed at 120,000 resolving power (m/z 400). Data-dependent top-N mass spectrometry was performed, with precursors selected from sequential 25-Da windows. HCD was performed twice on the same precursor, first by use of a quadrupole isolation width of 0.7 m/z for peptide identification, and then using 25 m/z quadrupole isolation. Fragment ions were analyzed in the Orbitrap at a mass resolving power of 120,000 (m/z 400). MS¹ and MS² target accumulation values were set to 2 × 10⁵ and 5 × 10⁴, respectively.

Data Analysis

Thermo.raw files were converted to searchable DTA text files using the Coon OMSSA Proteomic Analysis Software Suite (COMPASS) (35). DTA files containing exclusively y-ions were generated using an in-house algorithm. DTA files were searched against the UniProt yeast database (version 132) with Lys-C specificity using the Open Mass Spectrometry Search Algorithm (OMSSA), version 2.1.9 (36). Methionine oxidation was searched as a variable modification. Cysteine carbamidomethylation and the mass shift imparted by the lysine isotopolgues were searched as fixed modifications. For MS² scans performed at a resolving power of 60,000, 120,000, or 240,000, a shift of +8.0142, representing the mass shift of the ¹³C₆¹⁵N₂ isotopologue, was searched. For MS² scans performed at 15,000 resolving power, the average shift of the ¹³C₆¹⁵N₂ and ⁸H₂ isotopologues (+8.0322) was searched. For all analyses, the precursor mass was obtained from the 480,000 MS scan. The precursor mass tolerance was defined as 50 ppm, and the fragment ion mass tolerance was set to 0.01 Da. A histogram of precursor mass error at different search tolerances is presented in supplemental Fig. S1. Using the COMPASS software suite, obtained search results were filtered to 1% FDR based on E-values. y-ion doublets were extracted from raw files using an in-house algorithm explained in the supplemental information. Briefly, an ensemble of three different machine learning models was used to score each MS/MS spectral peak for C-terminal product ion prediction. To train our ensemble learner to correctly distinguish C-terminal product ion peaks from N-terminal product ion peaks and noise peaks within our experimental MS/MS spectra, we generated a representative training set of spectral data. Instances used for training and test sets were peaks acquired only from MS/MS spectra associated with a peptide identification. Peaks with a signal-to-noise value of less than 5 were not used. Feature information for each training/testing instance was extracted from raw spectral data. Seven MS/MS spectral features were selected to generate training and test set data: (1) “has doublet” (evaluated as “true” only if a spectral peak could be found at the predicted m/z of the peak''s “heavy” partner), (2) “signal-to-noise” (discretized using a scale of 1–5 based on the peak''s signal-to-noise value), (3) “is isotope,” (4) “is neutral loss,” (5) “number of isotopes,” (6) “number of doublet isotopes,” and (7) “has neutral loss.”To evaluate NeuCode SILAC labeling for automated de novo sequencing, PepNovo⁺ (8) was benchmarked on y-ion predicted spectra. First, a set of identified spectra from 13,832 unique peptides (>7,400 per precursor charge 2–3) was produced to train PepNovo⁺ so it could learn features such as the relative peak height ranks of b/y-ions and the probability of noise at each mass interval. These training spectra were acquired under the 11 NeuCode yeast strong cation exchange fractions prepared as described above. Thermo raw files were converted into mzXML format using ProteoWizard v2.2.2828 (with peak-picking turned on) and identified by MS-GF⁺ v9358 (37) at a 1% spectrum-level FDR against the UniProt yeast database (plus isoforms), v20110729. A fixed modification of K⁺8.0142 was imposed along with variable modifications of oxidized Met and deamidated Asn/Gln. All MS/MS scans were searched with a 50-ppm precursor mass tolerance, the high-accuracy LTQ instrument setting, the HCD fragmentation setting, and one allowed missed Lys-C cleavage.Thermo.raw files were also converted into DTA spectra as before, except the in-house algorithm for selecting y-ion doublets was slightly altered to boost the peak height of predicted y-ions above that of other peaks (the cumulative peak height was equal to the sum of the monoisotopic doublet peaks, all isotopic doublet peaks, and two times the peak height of the base peak) and to convert their m/z to charge one. Remaining peaks not predicted to be y-ions were converted to charge one by a previously described MS/MS deconvolution tool (38). Deconvoluted DTA spectra that originated from identified MS/MS scans were then paired with the MSGF⁺ peptide IDs and passed to PepNovo⁺ for training. The resulting PepNovo⁺ scoring model lacked the rank-boosting component (39), which requires identified spectra from >100,000 unique peptides per precursor charge state and extensive modification of the PepNovo⁺ source code to train. Still, the model was sufficient to perform de novo peptide sequencing on the y-ion predicted spectra. PepNovo⁺ was also run on the raw MS/MS scans (mzXML spectra converted to MGF with all MS/MS peaks converted to charge one) by use of a previously trained HCD scoring model that also lacks the rank-boosting component (40). The following PepNovo⁺ parameters were set at all stages of training and benchmarking: fixed modification of K⁺8.0142; variable modifications of oxidized Met and deamidated Asn; 0.01-Da fragment mass tolerance; use of spectrum precursor charge; and use of spectrum precursor m/z.     

Automatic validation of phosphopeptide identifications by the MS2/MS3 target-decoy search strategy

Manual checking is commonly employed to validate the phosphopeptide identifications from database searching of tandem mass spectra. It is very time-consuming and labor intensive as the number of phosphopeptide identifications increases greatly. In this study, a simple automatic validation approach was developed for phosphopeptide identification by combining consecutive stage mass spectrometry data and the target-decoy database searching strategy. Only phosphopeptides identified from both MS2 and its corresponding MS3 were accepted for further filtering, which greatly improved the reliability in phosphopeptide identification. Before database searching, the spectra were validated for charge state and neutral loss peak intensity, and then the invalid MS2/MS3 spectra were removed, which greatly reduced the database searching time. It was found that the sensitivity was significantly improved in MS2/MS3 strategy as the number of identified phosphopeptides was 2.5 times that obtained by the conventional filter-based MS2 approach. Because of the use of the target-decoy database, the false-discovery rate (FDR) of the identified phosphopeptides could be easily determined, and it was demonstrated that the determined FDR can precisely reflect the actual FDR without any manual validation stage.     

Evidence TRPV4 contributes to mechanosensitive ion channels in mouse skeletal muscle fibers

We recorded the activity of single mechanosensitive (MS) ion channels from membrane patches on single muscle fibers isolated from mice. We investigated the actions of various TRP (transient receptor potential) channel blockers on MS channel activity. 2-aminoethoxydiphenyl borate (2-APB) neither inhibited nor facilitated single channel activity at submillimolar concentrations. The absence of an effect of 2-APB indicates MS channels are not composed purely of TRPC or TRPV1, 2 or 3 proteins. Exposing patches to 1-oleolyl-2-acetyl-sn-glycerol (OAG), a potent activator of TRPC channels, also had no effect on MS channel activity. In addition, flufenamic acid and spermidine had no effect on the activity of single MS channels. By contrast, SKF-96365 and ruthenium red blocked single-channel currents at micromolar concentrations. SKF-96365 produced a rapid block of the open channel current. The blocking rate depended linearly on blocker concentration, while the unblocking rate was independent of concentration, consistent with a simple model of open channel block. A fit to the concentration-dependence of block gave k_on = 13 x 10⁶ M⁻¹s⁻¹ and k_off = 1609 sec⁻¹ with K_D = ~124 µM. Block by ruthenium red was complex, involving both reduction of the amplitude of the single-channel current and increased occupancy of subconductance levels. The reduction in current amplitude with increasing concentration of ruthenium red gave a K_D = ~49 µM. The high sensitivity of MS channels to block by ruthenium red suggests MS channels in skeletal muscle contain TRPV subunits. Recordings from skeletal muscle isolated from TRPV4 knockout mice failed to show MS channel activity, consistent with a contribution of TRPV4. In addition, exposure to hypo-osmotic solutions increases opening of MS channels in muscle. Our results provide evidence TRPV4 contributes to MS channels in skeletal muscle.     

Ultrasensitive determination of NE-100, a novel sigma ligand,in human plasma by liquid chromatography and electrospray ionization tandem mass spectrometry combined with a column-switching technique

For the highly sensitive and selective determination of NE-100, a novel sigma ligand, at levels of low picogram per milliliter of human plasma, a method with excellent reliability employing liquid chromatography (LC)–electrospray ionization (ESI) tandem mass spectrometry (MS–MS) combined with a column-switching technique has been developed. The method involves the use of a stable isotope labeled compound as the internal standard (I.S.), liquid–solid extraction of a plasma specimen with a C₈ cartridge, automated on-line clean-up on a short trapping column, subsequent separation on a micro-bore C₁₈ column and detection with ESI-MS–MS using m/z 356 ([M+H]⁺) as a precursor ion and m/z 105 as a product ion in a selected reaction monitoring mode. The detection and the quantification limits of NE-100 in plasma were 0.5 pg/ml with a signal-to-noise ratio (S/N) of 3 and 2.3 pg/ml, respectively, with an S/N of 21. The good linearity of the calibration graph was obtained in the range of 2.3∼907.0 pg/ml with excellent reliability. The developed method was applied to the determination of NE-100 in plasma obtained from the clinical trail.     

A Phos-tag-based fluorescence resonance energy transfer system for the analysis of the dephosphorylation of phosphopeptides

Fluorescence resonance energy transfer (FRET) is a distance-dependent interaction between the electronic excited states of two dye molecules. Here we introduce a novel FRET system for the detection of phosphopeptides using a phosphate-binding tag molecule, Zn²⁺-Phos-tag (1,3-bis[bis(pyridin-2-ylmethyl)amino]propan-2-olato dizinc(II) complex) attached with a 7-amino-4-methylcoumarin-3-acetic acid (AMCA). Carboxyfluorescein (FAM)-labeled phospho- and nonphosphopeptides were prepared as the target molecules for the FRET system. A set of FAM (a fluorescent acceptor, λ_em 520 nm) and AMCA (a fluorescent donor, λ_ex 345 nm) is frequently used for a FRET system. The AMCA-labeled Zn²⁺-Phos-tag specifically captured the FAM-labeled phosphopeptide to form a stable 1:1 complex, resulting in efficient FRET. After the FAM-labeled phosphopeptide was dephosphorylated with alkaline phosphatase, the FRET disappeared. Using this FRET system, we demonstrated the detection of the time-dependent dephosphorylation of the FAM-labeled protein-tyrosine phosphatase 1B substrate.     

Chemical derivatization of phosphoserine and phosphothreonine containing peptides to increase sensitivity for MALDI-based analysis and for selectivity of MS/MS analysis

Protein phosphorylation is one of the most important and common ways of regulating protein function in cells. However, phosphopeptides are difficult to analyse, ionising poorly under standard MALDI conditions. Several methods have been developed to deal with the low sensitivity and specificity of phosphopeptide analysis. Here, we show an approach using a simple one-step beta-elimination/Michael addition reaction for the derivatization of phosphoserine and phosphothreonine. The substitution of the negatively charged phosphate group by a positively charged S-ethylpyridyl group greatly improves the ionisation of the modified peptides, especially in MALDI MS, increasing the sensitivity of the analysis. The modification allows the formation of a unique fragment ion at m/z 106 under mild collisional activation conditions, which can be used for parent (precursor) ion scanning in order to improve both the sensitivity and the selectivity of the analysis. The optimisation of the approach is described for a standard model peptide and protein and then applied to phosphorylation analysis in two biologically derived proteins purified from different experimental systems.