Increased throughput of proteomics analysis by multiplexing high-resolution tandem mass spectra

High-resolution and high-accuracy Fourier transform mass spectrometry (FTMS) is becoming increasingly attractive due to its specificity. However, the speed of tandem FTMS analysis severely limits the competitive advantage of this approach relative to faster low-resolution quadrupole ion trap MS/MS instruments. Here we demonstrate an entirely FTMS-based analysis method with a 2.5-3.0-fold greater throughput than a conventional FT MS/MS approach. The method consists of accumulating together the MS/MS fragments ions from multiple precursors, with subsequent high-resolution analysis of the mixture. Following acquisition, the multiplexed spectrum is deconvoluted into individual MS/MS spectra which are then combined into a single concatenated file and submitted for peptide identification to a search engine. The method is tested both in silico using a database of MS/MS spectra as well as in situ using a modified LTQ Orbitrap mass spectrometer. The performance of the method in the experiment was consistent with theoretical expectations.     

Hadamard transform measurement of tandem Fourier-transform mass spectra

The simultaneous collection of multiple spectra using tandem (MS/MS) and multidimensional (MS/MS/MS) mass spectrometry from multiple precursors is demonstrated to yield correspondingly enhanced sensitivity. This approach utilizes Hadamard transform deconvolution and takes advantage of the multichannel dissociation capability of Fourier-transform mass spectrometry. By application of this to an 11-component mixture, the 11 spectra of the products of dissociating 11 different combinations of six of the component molecular ions are measured; Hadamard transformation yields individual spectra of the precursor ions exhibiting a signal-to-noise improvement of 1.8x over spectra measured separately, as predicted by theory. Precursor ion selection with high specificity and product formation with high abundance reproducibility are critical; spurious peaks resulting from imperfect reproducibility can be minimized by using simultaneous equation coefficients reflecting the degree of precursor dissociation. Extension of this technique to MSn spectra is demonstrated with simultaneous MS/MS/MS monitoring of three precursors and three daughters yielding nine spectra representing the nine possible dissociation pathways. For MSn spectra, coding the product relationships for each additional step (e.g., precursor----daughter, daughter----granddaughter) requires elimination of half of the remaining ions. No ions are lost for coding in an improved Hadamard approach in which the combined daughter spectrum of the selected half of the precursors is subtracted from that of the other half.     

Lookup peaks: a hybrid of de novo sequencing and database search for protein identification by tandem mass spectrometry

A powerful technique for peptide and protein identification is tandem mass spectrometry followed by database search using a program such as SEQUEST or Mascot. These programs, however, become slow and lose sensitivity when allowing nonspecific cleavages or peptide modifications. De novo sequencing and hybrid methods such as sequence tagging offer speed and robustness for wider searches, yet these approaches require better spectra with more complete and consecutive fragmentation and, hence, are less sensitive to low-abundance peptides. Here we describe a new hybrid method that retains the sensitivity of pure database search. The method uses a small amount of de novo analysis to identify likely b- and y-ion peaks--"lookup peaks"--that can then be used to extract candidate peptides from the database, with the number of candidates tunable to fit a computing budget. We describe a program called ByOnic that implements this method, and we benchmark ByOnic on several data sets, including one of mouse blood plasma spiked with low concentrations of recombinant human proteins. We demonstrate that ByOnic is more sensitive than sequence tagging and, indeed, more sensitive than the three most popular pure database search tools--SEQUEST, Mascot, and X!Tandem--on both the peptide and protein levels. On the mouse plasma samples, ByOnic consistently found spiked proteins missed by the other tools.     

Implementation and uses of automated de novo peptide sequencing by tandem mass spectrometry

There are several computer programs that can match peptide tandem mass spectrometry data to their exactly corresponding database sequences, and in most protein identification projects, these programs are utilized in the early stages of data interpretation. However, situations frequently arise where tandem mass spectral data cannot be correlated with any database sequences. In these cases, the unmatched data could be due to peptides derived from novel proteins, allelic or species-derived variants of known proteins, or posttranslational or chemical modifications. Two additional problems are frequently encountered in high-throughput protein identification. First, it is difficult to quickly sift through large amounts of data to identify those spectra that, due to poor signal or contaminants, can be ignored. Second, it is important to find incorrect database matches (false positives). We have chosen to address these difficulties by performing automatic de novo sequencing using a computer program called Lutefisk. Sequence candidates obtained are used as input in a homology-based database search program called CIDentify to identify variants of known proteins. Comparison of database-derived sequences with de novo sequences allows for electronic validation of database matches even if the latter are not completely correct. Modifications to the original Lutefisk program have been implemented to handle data obtained from triple quadrupole, ion trap, and quadrupole/time-of-flight hybrid (Qtof) mass spectrometers. For example, the linearity of mass errors due to temperature-dependent expansion of the flight tube in a Qtof was exploited such that isobaric amino acids (glutamine/lysine and oxidized methionine/ phenylalanine) can be differentiated without careful attention to mass calibration.     

Automatic validation of phosphopeptide identifications from tandem mass spectra

We developed and compared two approaches for automated validation of phosphopeptide tandem mass spectra identified using database searching algorithms. Phosphopeptide identifications were obtained through SEQUEST searches of a protein database appended with its decoy (reversed sequences). Statistical evaluation and iterative searches were employed to create a high-quality data set of phosphopeptides. Automation of postsearch validation was approached by two different strategies. By using statistical multiple testing, we calculate a p value for each tentative peptide phosphorylation. In a second method, we use a support vector machine (SVM; a machine learning algorithm) binary classifier to predict whether a tentative peptide phosphorylation is true. We show good agreement (85%) between postsearch validation of phosphopeptide/spectrum matches by multiple testing and that from support vector machines. Automatic methods conform very well with manual expert validation in a blinded test. Additionally, the algorithms were tested on the identification of synthetic phosphopeptides. We show that phosphate neutral losses in tandem mass spectra can be used to assess the correctness of phosphopeptide/spectrum matches. An SVM classifier with a radial basis function provided classification accuracy from 95.7% to 96.8% of the positive data set, depending on search algorithm used. Establishing the efficacy of an identification is a necessary step for further postsearch interrogation of the spectra for complete localization of phosphorylation sites. Our current implementation performs validation of phosphoserine/phosphothreonine-containing peptides having one or two phosphorylation sites from data gathered on an ion trap mass spectrometer. The SVM-based algorithm has been implemented in the software package DeBunker. We illustrate the application of the SVM-based software DeBunker on a large phosphorylation data set.     

CIFTER: automated charge-state determination for peptide tandem mass spectra

Tandem mass spectrometry (MS/MS) has become a common and useful tool for analyzing complex protein mixtures. Database search programs are the most popular means for peptide identification from MS/MS spectra. However, estimations of charge states of peptide MS/MS spectra obtained from low-resolution mass spectrometers have not been reliable. They require repetitive database searches and additional analyses of the search results. We propose here an algorithm designed to reliably differentiate doubly charged spectra from triply charged ones. We conducted a rigorous analysis of various spectral features and their effects. We employed the distinguishing features found in our analysis and developed a classifier for multiply charged spectra using a machine learning approach. The test on various data sets showed that our method could be successfully applied independent of experimental setup and mass instrument. This algorithm can be used to prefilter spectra so that only reasonably good spectra are submitted to database search programs, thereby saving considerable time. The software for MS/MS charge-state determination, which we named "CIFTER", is available at a website http://prix.uos.ac.kr/sifter/cifter.     

Versatile online-offline engine for automated acquisition of high-resolution tandem mass spectra

For automated production of tandem mass spectrometric data for proteins and peptides >3 kDa at >50 000 resolution, a dual online-offline approach is presented here that improves upon standard liquid chromatography-tandem mass spectrometry (LC-MS/MS) strategies. An integrated hardware and software infrastructure analyzes online LC-MS data and intelligently determines which targets to interrogate offline using a posteriori knowledge such as prior observation, identification, and degree of characterization. This platform represents a way to implement accurate mass inclusion and exclusion lists in the context of a proteome project, automating collection of high-resolution MS/MS data that cannot currently be acquired on a chromatographic time scale at equivalent spectral quality. For intact proteins from an acid extract of human nuclei fractionated by reversed-phase liquid chromatography (RPLC), the automated offline system generated 57 successful identifications of protein forms arising from 30 distinct genes, a substantial improvement over online LC-MS/MS using the same 12 T LTQ FT Ultra instrument. Analysis of human nuclei subjected to a shotgun Lys-C digest using the same RPLC/automated offline sampling identified 147 unique peptides containing 29 co- and post-translational modifications. Expectation values ranged from 10 (-5) to 10 (-99), allowing routine multiplexed identifications.     

InsPecT: identification of posttranslationally modified peptides from tandem mass spectra

Reliable identification of posttranslational modifications is key to understanding various cellular regulatory processes. We describe a tool, InsPecT, to identify posttranslational modifications using tandem mass spectrometry data. InsPecT constructs database filters that proved to be very successful in genomics searches. Given an MS/MS spectrum S and a database D, a database filter selects a small fraction of database D that is guaranteed (with high probability) to contain a peptide that produced S. InsPecT uses peptide sequence tags as efficient filters that reduce the size of the database by a few orders of magnitude while retaining the correct peptide with very high probability. In addition to filtering, InsPecT also uses novel algorithms for scoring and validating in the presence of modifications, without explicit enumeration of all variants. InsPecT identifies modified peptides with better or equivalent accuracy than other database search tools while being 2 orders of magnitude faster than SEQUEST, and substantially faster than X!TANDEM on complex mixtures. The tool was used to identify a number of novel modifications in different data sets, including many phosphopeptides in data provided by Alliance for Cellular Signaling that were missed by other tools.     

Cross-correlation algorithm for calculation of peptide molecular weight from tandem mass spectra

We have developed an approach to identify the molecular weight of a peptide ion directly from its corresponding tandem mass spectrum using a cross-correlation function. We have shown that the monoisotopic molecular weight can be calculated for approximately 90% of tandem mass spectra identified from tryptic digests of complex protein mixtures. The accuracy of the calculated monoisotopic masses was dependent on the resolution and mass accuracy of the spectra analyzed, but was typically <0.25 amu for linear ion trap mass spectra. The ability to calculate accurate monoisotopic molecular weights for low-resolution ion trap data should significantly improve both the speed and performance of database searches for which typical mass accuracies of approximately 3 amu are employed. In addition, this strategy can also be used to identify the precursor ion for tandem mass spectra acquired using large ion selection windows in data-independent collision-activated dissociation and has the potential to identify multiplexed tandem mass spectra.     

Statistical characterization of ion trap tandem mass spectra from doubly charged tryptic peptides

Collision-induced dissociation (CID) is a common ion activation technique used to energize mass-selected peptide ions during tandem mass spectrometry. Characteristic fragment ions form from the cleavage of amide bonds within a peptide undergoing CID, allowing the inference of its amino acid sequence. The statistical characterization of these fragment ions is essential for improving peptide identification algorithms and for understanding the complex reactions taking place during CID. An examination of 1465 ion trap spectra from doubly charged tryptic peptides reveals several trends important to understanding this fragmentation process. While less abundant than y ions, b ions are present in sufficient numbers to aid sequencing algorithms. Fragment ions exhibit a characteristic series-specific relationship between their masses and intensities. Each residue influences fragmentation at adjacent amide bonds, with Pro quantifiably enhancing cleavage at its N-terminal amide bond and His increasing the formation of b ions at its C-terminal amide bond. Fragment ions corresponding to a formal loss of ammonia appear preferentially in peptides containing Gln and Asn. These trends are partially responsible for the complexity of peptide tandem mass spectra.     

Impact of ion trap tandem mass spectra variability on the identification of peptides

Peptide identification based on tandem mass spectrometry and database searching algorithms has become one of the central technologies in proteomics. At the heart of this technology is the ability to reproducibly acquire high-quality tandem mass spectra for database interrogation. The variability in tandem mass spectra generation is often assumed to be minimal, and peptide identifications are typically based on a single tandem mass spectrum. In this paper, we characterize the variance of scores derived from replicate tandem mass spectra using several database search algorithms and demonstrate the effects of spectral variability on the correct identification of peptides. We show that the variance associated with the collection of tandem mass spectra can be substantial leading to sizable errors in search algorithm scores ( approximately 5-25% RSD) and ultimately incorrect assignments. Processing strategies are discussed to minimize the impact of tandem mass spectra variability on peptide identification.     

Peptide sequencing and characterization of post-translational modifications by enhanced ion-charging and liquid chromatography electron-transfer dissociation tandem mass spectrometry

We have tested the effect of m-nitrobenzyl alcohol (m-NBA) as a method to increase the average charge state of protonated gas-phase molecular ions generated by ESI from tryptic peptides and phosphopeptides. Various concentrations of m-NBA were added to the mobile phases of a liquid chromatography system coupled to an ESI tandem mass spectrometer. Addition of just 0.1% m-NBA changed the average charge state for the identified tryptic BSA peptides from 2.2+ to 2.6+. As a result, the predominant charge states for BSA peptides were changed from 2+ to > or =3+. To evaluate the benefits of peptide charge enhancement, the ETD fragmentation efficiency and Mascot peptide score were compared for BSA peptides in charge states 2+ and 3+. In all cases but one, triply charged peptides fragmented more efficiently than the analogues 2+ peptide ions. On average, triply charged peptides received a 68% higher Mascot score (24 units) than doubly charged peptides. m-NBA also increased the average charge state of phosphopeptides by up to 0.5 charge unit. The ease of implementation and the analytical benefits of charge enhancement of tryptic peptides by addition of m-NBA to the LC solvents suggest the general application of this reagent in proteomic studies that employ ETD-MS/MS and related techniques.     

Spatially resolved protein hydrogen exchange measured by subzero-cooled chip-based nanoelectrospray ionization tandem mass spectrometry

Mass spectrometry has become a valuable method for studying structural dynamics of proteins in solution by measuring their backbone amide hydrogen/deuterium exchange (HDX) kinetics. In a typical exchange experiment one or more proteins are incubated in deuterated buffer at physiological conditions. After a given period of deuteration, the exchange reaction is quenched by acidification (pH 2.5) and cooling (0 °C) and the deuterated protein (or a digest thereof) is analyzed by mass spectrometry. The unavoidable loss of deuterium (back-exchange) that occurs under quench conditions is undesired as it leads to loss of information. Here we describe the successful application of a chip-based nanoelectrospray ionization mass spectrometry top-down fragmentation approach based on cooling to subzero temperature (-15 °C) which reduces the back-exchange at quench conditions to very low levels. For example, only 4% and 6% deuterium loss for fully deuterated ubiquitin and β(2)-microglobulin were observed after 10 min of back-exchange. The practical value of our subzero-cooled setup for top-down fragmentation HDX analyses is demonstrated by electron-transfer dissociation of ubiquitin ions under carefully optimized mass spectrometric conditions where gas-phase hydrogen scrambling is negligible. Our results show that the known dynamic behavior of ubiquitin in solution is accurately reflected in the deuterium contents of the fragment ions.     

Identification of phosphoserine and phosphothreonine as cysteic acid and beta-methylcysteic acid residues in peptides by tandem mass spectrometric sequencing

Tandem mass spectrometry has long been an intrinsic tool to determine phosphorylation sites in proteins. However, loss of the phosphate moiety from both phosphoserine and phosphothreonine residues in low-energy collision-induced dissociation is a common phenomenon, which makes identification of P-Ser and P-Thr residues complicated. A method for direct sequencing of the Ser and Thr phosphorylation sites by ESI tandem mass spectrometry following beta-elimination/sulfite addition to convert -HPO4 to -SO3 has been studied. Five model phosphopeptides, including three synthetic P-Ser-, P-Thr-, or P-Ser- and P-Thr-containing peptides; a protein kinases C-phosphorylated peptide; and a phosphopeptide derived from beta-casein trypsin digests were modified and then sequenced using an ESI-quadrupole ion trap mass spectrometer. Following incubation of P-Ser- or P-Thr-containing peptides with Na2SO3/NaOH, 90% P-Ser and 80% P-Thr was converted to cysteic acid and beta-methylcysteic acid, respectively, as revealed by amino acid analysis. The conversion can be carried out at 1 microM concentration of the peptide. Both cysteic acid and beta-methylcysteic acid residues in the sequence were shown to be stable and easily identifiable under general conditions for tandem mass spectrometric sequencing applicable to common peptides.     

Cleavage N-terminal to proline: analysis of a database of peptide tandem mass spectra

Fragmentation at the Xxx-Pro bond was analyzed for a group of peptide mass spectra that were acquired in a Finnigan ion trap mass spectrometer and were generated from proteins digested by enzymes and identified by the Sequest algorithm. Cleavage with formation of a + b + y ions occurred more readily at the Xxx-Pro bond than at other locations in these peptides, and the importance of this cleavage varied by the identity of Xxx. The most abundant Xxx-Pro relative bond cleavage ratios were observed when Xxx was Val, His, Asp, Ile, and Leu, whereas the least abundant cleavage ratios occurred when Xxx was Gly or Pro. Rationalization for these cleavage ratios at Xxx-Pro may include contribution of the Asp or His side chain to enhanced cleavage or the conformation of Pro, Gly, and the aliphatic residues Val, Ile, and Leu at the Xxx location in the Xxx-Pro bond. Although unusual fragmentation behavior has been noted for Pro-containing peptides, this analysis suggests that fragmentation at the Xxx-Pro bond is predictable and that this information may be used to improve the identification of proteins if it is incorporated into peptide sequencing algorithms.     

Statistical model for large-scale peptide identification in databases from tandem mass spectra using SEQUEST

Recent technological advances have made multidimensional peptide separation techniques coupled with tandem mass spectrometry the method of choice for high-throughput identification of proteins. Due to these advances, the development of software tools for large-scale, fully automated, unambiguous peptide identification is highly necessary. In this work, we have used as a model the nuclear proteome from Jurkat cells and present a processing algorithm that allows accurate predictions of random matching distributions, based on the two SEQUEST scores Xcorr and DeltaCn. Our method permits a very simple and precise calculation of the probabilities associated with individual peptide assignments, as well as of the false discovery rate among the peptides identified in any experiment. A further mathematical analysis demonstrates that the score distributions are highly dependent on database size and precursor mass window and suggests that the probability associated with SEQUEST scores depends on the number of candidate peptide sequences available for the search. Our results highlight the importance of adjusting the filtering criteria to discriminate between correct and incorrect peptide sequences according to the circumstances of each particular experiment.     

MSNovo: a dynamic programming algorithm for de novo peptide sequencing via tandem mass spectrometry

Tandem mass spectrometry (MS/MS) has become the experimental method of choice for high-throughput proteomics-based biological discovery. The two primary ways of analyzing MS/MS data are database search and de novo sequencing. In this paper, we present a new approach to peptide de novo sequencing, called MSNovo, which has the following advanced features. (1) It works on data generated from both LCQ and LTQ mass spectrometers and interprets singly, doubly, and triply charged ions. (2) It integrates a new probabilistic scoring function with a mass array-based dynamic programming algorithm. The simplicity of the scoring function, with only 6-10 parameters to be trained, avoids the problem of overfitting and allows MSNovo to be adopted for other machines and data sets easily. The mass array data structure explicitly encodes all possible peptides and allows the dynamic programming algorithm to find the best peptide. (3) Compared to existing programs, MSNovo predicts peptides as well as sequence tags with a higher accuracy, which is important for those applications that search protein databases using the de novo sequencing results. More specifically, we show that MSNovo outperforms other programs on various ESI ion trap data. We also show that for high-resolution data the performance of MSNovo improves significantly. Supporting Information, executable files and data sets can be found at http://msms.usc.edu/supplementary/msnovo.     

Identification of protein ubiquitylation by electrospray ionization tandem mass spectrometric analysis of sulfonated tryptic peptides

We report here the application of electrospray ionization tandem mass spectrometry for the characterization of protein ubiquitylation, an important posttranslational modification of cellular proteins. Trypsin digestion of ubiquitin-conjugated proteins produces diglycine branched peptides containing the modification sites. Chemical derivatization by N-terminal sulfonation was carried out on several model peptides for the formation of a characteristic fragmentation pattern in their MS/MS analysis. The fragmentation of derivatized singly charged peptides results in a product ion distribution similar to that already observed by MALDI-TOF MS/MS. Signature fragments distinguished the diglycine branched peptides from other modified and unmodified peptides, while the sequencing product ions reveal the amino acid sequence and the location of the ubiquitylation site. Doubly charged peptide derivatives fragment in a somewhat different manner, but several fragments characteristic to diglycine branched peptides were observed under low collision energy conditions. These signature peaks can also be used to identify peptides containing ubiquitylation sites. In addition, a marker ion corresponding to a glycine-modified lysine residue produced by high-energy fragmentation provides useful information for identity verification. The method is demonstrated by the analysis of three ubiquitin-conjugated proteins using LC/MS/MS.     

Consecutive ion activation for top down mass spectrometry: improved protein sequencing by nozzle-skimmer dissociation

Mass spectra produced by nozzle-skimmer dissociation (NSD) have been little used in the past for structural characterization. NSD cannot be used on mass-separated ions (MS/MS), and for electrosprayed protein ions, previous NSD spectra showed backbone cleavages similar to those from energetic methods such as collisionally activated dissociation (CAD) or infrared multiphoton dissociation (IRMPD). However, our experimental configuration with Fourier transform (FT) MS makes possible three consecutive steps of NSD ion activation: thermal in the entrance capillary and collisional in both the nozzle-skimmer (N-S) region and the region after the skimmer before the quadrupole entrance lens (S-Q). In the high-pressure N-S region of adjustable path length, ions undergo high-frequency, low-energy collisions to rupture weak noncovalent or covalent bonds, with these "denatured" products then subjected to high-energy collisions in the low-pressure S-Q region to cleave strong backbone bonds. These NSD spectra, plus those from variable capillary thermal activation, of 8+ to 11+ ubiquitin ions electrosprayed from denatured solution show backbone cleavages between 74 of 75 amino acid pairs, vs 66 for CAD and 50 for IRMPD in the FTMS cell. Thermal activation by the inlet capillary of the newly desolvated 6+, 7+ ubiquitin ions from electrospraying the native conformer increases the NSD yield from 8% at 56 degrees C to 96% at 76 degrees C, but with little change in product branching ratios; this capillary heating has no effect on CAD or IRMPD of these ions collected in the FTMS cell. Ion desolvation with its concomitant H-bond strengthening appears to produce a transiently stable conformer whose formation can be prevented by capillary heating. The far more complex and stable noncovalent tertiary structures of large protein ions in the gas phase have made MS/MS difficult; initial inhibition of tertiary structure formation with immediate NSD ("prefolding dissociation") appears promising for the top down characterization of a 200-kDa protein.