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.     

Quantitative comparison of proteomic data quality between a 2D and 3D quadrupole ion trap

A 2D ion trap has a greater ion trapping efficiency, greater ion capacity before observing space-charging effects, and a faster ion ejection rate than a traditional 3D ion trap mass spectrometer. These hardware improvements should result in a significant increase in protein identifications from complex mixtures analyzed using shotgun proteomics. In this study, we compare the quality and quantity of peptide identifications using data-dependent acquisition of tandem mass spectra of peptides between two commercially available ion trap mass spectrometers (an LTQ and an LCQ XP Max). We demonstrate that the increased trapping efficiency, increased ion capacity, and faster ion ejection rate of the LTQ results in greater than 5-fold more protein identifications, better identification of low-abundance proteins, and higher confidence protein identifications when compared with a LCQ XP Max.     

Increased identification of peptides by enhanced data processing of high-resolution MALDI TOF/TOF mass spectra prior to database searching

This paper presents application of sequential enhanced data processing procedures to high-resolution tandem mass spectra for identification of peptides using the Mascot database search algorithm. A strategy for (1) selection of fragment ion peaks from MS/MS spectra, (2) utilization of improved mass accuracy of the precursor ions, and (3) wavelet denoising of the mass spectra prior to fragment ion selection have been developed. The number of peptide identifications obtained using the enhanced processing was then compared with that obtained using software provided by the instrument manufacturer. Approximately 9000 MS/MS spectra acquired by the Applied Biosystems 4700 TOF/TOF MS instrument were used as a model data set. After application of the new processing, an increase of 33% unique peptides and 22% protein identifications with at least two unique peptides were found. The influence of the processing on the percentage of false positives, estimated by searching against a randomized database, was estimated to increase false positive identifications from 2.7 to 3.9%, which was still below the 5% error rate specified in the Mascot search. These data processing approaches increase the amount of information that can be extracted from LC-MS analysis without the necessity of additional experiments.     

Performance of a linear ion trap-Orbitrap hybrid for peptide analysis

Proteomic analysis of digested complex protein mixtures has become a useful strategy to identify proteins involved in biological processes. We have evaluated the use of a new mass spectrometer that combines a linear ion trap and an Orbitrap to create a hybrid tandem mass spectrometer. A digested submandibular/sublingual saliva sample was used for the analysis. We find the instrument is capable of mass resolution in excess of 40,000 and mass measurement accuracies of less than 2 ppm for the analysis of complex peptide mixtures. Such high mass accuracy allowed the elimination of virtually any false positive peptide identifications, suggesting that peptides that do not match the specificity of the protease used in the digestion of the sample should not automatically be considered as false positives. Tandem mass spectra from the linear ion trap and from the Orbitrap have very similar ion abundance ratios. We conclude this instrument will be well suited for shotgun proteomic types of analyses.     

Multiplexed MS/MS in a quadrupole ion trap mass spectrometer

A multiplexing method for performing MS/MS on multiple peptide ions simultaneously in a quadrupole ion trap mass spectrometer (QITMS) has been developed. This method takes advantage of the inherent mass bias associated with ion accumulation in the QITMS to encode the intensity of precursor ions in a way that allows the corresponding product ions to be identified. The intensity encoding scheme utilizes the Gaussian distributions that characterize the relationship between ion intensities and rf trapping voltages during ion accumulation. This straightforward approach uses only two arbitrary waveforms, one for isolation and one for dissociation, to gather product ion spectra from N precursor ions in as little as two product ion spectra. In the example used to illustrate this method, 66% of the product ions from five different precursor peptide ions were correctly correlated using the multiplexing approach. Of the remaining 34% of the product ions, only 6% were misidentified, while 28% of the product ions failed to be identified because either they had too low intensity or they had the same m/z ratio as one of the precursor ions or the same m/z ratio as a product ion from a different precursor ion. This method has the potential to increase sample throughput, reduce total analysis times, and increase signal-to-noise ratios as compared to conventional MS/MS methods.     

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.     

Imaging MS methodology for more chemical information in less data acquisition time utilizing a hybrid linear ion trap-orbitrap mass spectrometer

A novel mass spectrometric imaging method is developed to reduce the data acquisition time and provide rich chemical information using a hybrid linear ion trap-orbitrap mass spectrometer. In this method, the linear ion trap and orbitrap are used in tandem to reduce the acquisition time by incorporating multiple linear ion trap scans during an orbitrap scan utilizing a spiral raster step plate movement. The data acquisition time was decreased by 43-49% in the current experiment compared to that of orbitrap-only scans; however, 75% or more time could be saved for higher mass resolution and with a higher repetition rate laser. Using this approach, a high spatial resolution of 10 μm was maintained at ion trap imaging, while orbitrap spectra were acquired at a lower spatial resolution, 20-40 μm, all with far less data acquisition time. Furthermore, various MS imaging methods were developed by interspersing MS/MS and MS(n) ion trap scans during orbitrap scans to provide more analytical information on the sample. This method was applied to differentiate and localize structural isomers of several flavonol glycosides from an Arabidopsis flower petal in which MS/MS, MS(n), ion trap, and orbitrap images were all acquired in a single data acquisition.     

Mining a tandem mass spectrometry database to determine the trends and global factors influencing peptide fragmentation

A database of 5500 unique peptide tandem mass spectra acquired in an ion trap mass spectrometer was assembled for peptides derived from proteins digested with trypsin. Peptides were identified initially from their tandem mass spectra by the SEQUEST algorithm and subsequently validated manually. Two different statistical methods were used to identify sequence-dependent fragmentation patterns that could be used to improve fragmentation models incorporated into current peptide sequencing and database search algorithms. The currently accepted "mobile proton" model was expanded to derive a new classification scheme for peptide mass spectra, the "relative proton mobility" scale, which considers peptide ion charge state and amino acid composition to categorize peptide mass spectra into peptide ions containing "nonmobile", "partially mobile", or "mobile" protons. Quantitation of amide bond fragmentation, both N- and C-terminal to any given amino acid, as well as the positional effect of an amino acid in a peptide and peptide length on such fragmentation, has been determined. Peptide bond cleavage propensities, both positive (i.e., enhanced) and negative (i.e., suppressed), were determined and ranked in order of their cleavage preferences as primary, secondary, or tertiary cleavage effects. For example, primary positive cleavage effects were observed for Xaa-Pro and Asp-Xaa bond cleavage for mobile and nonmobile peptide ion categories, respectively. We also report specific pairwise interactions (e.g., Asn-Gly) that result in enhanced amide bond cleavages analogous to those observed in solution-phase chemistry. Peptides classified as nonmobile gave low or insignificant scores, below reported MS/MS score thresholds (cutoff filters), indicating that incorporation of the relative proton mobility scale classification would lead to improvements in current MS/MS scoring functions.     

Statistical models for protein validation using tandem mass spectral data and protein amino acid sequence databases

The purpose of this work is to develop and verify statistical models for protein identification using peptide identifications derived from the results of tandem mass spectral database searches. Recently we have presented a probabilistic model for peptide identification that uses hypergeometric distribution to approximate fragment ion matches of database peptide sequences to experimental tandem mass spectra. Here we apply statistical models to the database search results to validate protein identifications. For this we formulate the protein identification problem in terms of two independent models, two-hypothesis binomial and multinomial models, which use the hypergeometric probabilities and cross-correlation scores, respectively. Each database search result is assumed to be a probabilistic event. The Bernoulli event has two outcomes: a protein is either identified or not. The probability of identifying a protein at each Bernoulli event is determined from relative length of the protein in the database (the null hypothesis) or the hypergeometric probability scores of the protein's peptides (the alternative hypothesis). We then calculate the binomial probability that the protein will be observed a certain number of times (number of database matches to its peptides) given the size of the data set (number of spectra) and the probability of protein identification at each Bernoulli event. The ratio of the probabilities from these two hypotheses (maximum likelihood ratio) is used as a test statistic to discriminate between true and false identifications. The significance and confidence levels of protein identifications are calculated from the model distributions. The multinomial model combines the database search results and generates an observed frequency distribution of cross-correlation scores (grouped into bins) between experimental spectra and identified amino acid sequences. The frequency distribution is used to generate p-value probabilities of each score bin. The probabilities are then normalized with respect to score bins to generate normalized probabilities of all score bins. A protein identification probability is the multinomial probability of observing the given set of peptide scores. To reduce the effect of random matches, we employ a marginalized multinomial model for small values of cross-correlation scores. We demonstrate that the combination of the two independent methods provides a useful tool for protein identification from results of database search using tandem mass spectra. A receiver operating characteristic curve demonstrates the sensitivity and accuracy level of the approach. The shortcomings of the models are related to the cases when protein assignment is based on unusual peptide fragmentation patterns that dominate over the model encoded in the peptide identification process. We have implemented the approach in a program called PROT_PROBE.     

Using statistical models to identify factors that have a role in defining the abundance of ions produced by tandem MS

A database of 5448 peptide tandem mass spectra acquired in a quadrupole time-of-flight mass spectrometer was generated for peptides derived from proteins digested with trypsin. Peptides were identified from their mass spectra by the Mascot algorithm. Statistical models were then used to investigate factors influencing the abundance of ions formed. Separate models were formulated for b and y ions as it was thought that different factors may influence the formation of each type of ion. Several factors were found to have a highly significant influence on the abundance of ions formed. These include the actual mass of the ion formed after fragmentation as well as the location of the cleavage. The composition of the fragmenting peptide was also found to be important, and amino acids either side of the fragmentation site influenced the abundance of ions produced. To increase understanding of fragmentation mechanisms, the effect of several physicochemical properties of these residues was also investigated in a separate model. In conclusion, the models formulated for b and y ions provide useful characterization of the abundance of ions formed, and this information could be used to develop improved algorithms for peptide identification.     

Whole protein dissociation in a quadrupole ion trap: identification of an a priori unknown modified protein

A protein mixture derived from a whole cell lysate fraction of Saccharomyces cerevisiae, which contains roughly 19 proteins, has been analyzed to identify an a priori unknown modified protein using a quadrupole ion trap tandem mass spectrometer. Collection of the experimental data was facilitated by collision-induced dissociation and ion/ion proton-transfer reactions in multistage mass spectrometry procedures. Ion/ion reactions were used to manipulate charge states of both parent ions and product ions for the purpose of concentrating charge into the parent ion of interest and to reduce the product ion charge states for determination of product ion mass and abundance. The identification of the protein was achieved by matching the uninterpreted product ion spectrum against protein sequence databases with varying degrees of annotation, coupled with a scoring scheme weighted for the relative abundances of the experimentally observed product ions and the frequency of fragmentations occurring at preferential sites. The protein was identified to be an acetylated yeast heat shock protein, HS12_Yeast (11.6 kDa), with the initiating methionine residue removed. This constitutes the first example of the identification of an a priori unknown protein that is not present in an annotated protein database using a "top-down" approach with a quadrupole ion trap. This example illustrates the utility of relatively low cost instrumentation with modest mass analysis characteristics for the identification of modified proteins without recourse to enzymatic digestion. It also illustrates how experimental data can be used interactively with protein databases when the modified protein of interest is not initially present in the database.     

Similarity among tandem mass spectra from proteomic experiments: detection,significance, and utility

Liquid chromatography paired with tandem mass spectrometry is a standard technique for identifying peptides from complex protein mixtures. Most fragment ion spectra acquired by this technique are unique, but some are repeated. Similarities among the spectra from 1D and 2D liquid chromatography experiments were calculated by the dot product algorithm. Similar spectra were grouped, and the degree of duplication was calculated for each sample. In 1D liquid chromatography data from 1D gel bands, 18% of the fragment ion spectra were duplicates. A six-cycle 2D liquid chromatographic separation of more than 200 proteins produced 28% duplicate spectra. A rat hippocampal homogenate analyzed by a 12-cycle 2D liquid chromatographic separation contained 25% duplicate spectra. Removal of these duplicate spectra, however, resulted in fewer peptides being successfully identified by SEQUEST. We propose a modification for peptide identification algorithms that would improve their performance and accuracy by explicitly recognizing and making use of spectral similarity.     

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.     

Probability-based validation of protein identifications using a modified SEQUEST algorithm

Database-searching algorithms compatible with shotgun proteomics match a peptide tandem mass spectrum to a predicted mass spectrum for an amino acid sequence within a database. SEQUEST is one of the most common software algorithms used for the analysis of peptide tandem mass spectra by using a cross-correlation (XCorr) scoring routine to match tandem mass spectra to model spectra derived from peptide sequences. To assess a match, SEQUEST uses the difference between the first- and second-ranked sequences (ACn). This value is dependent on the database size, search parameters, and sequence homologies. In this report, we demonstrate the use of a scoring routine (SEQUEST-NORM) that normalizes XCorr values to be independent of peptide size and the database used to perform the search. This new scoring routine is used to objectively calculate the percent confidence of protein identifications and posttranslational modifications based solely on the XCorr value.     

Protocol for an electrospray ionization tandem mass spectral product ion library: development and application for identification of 240 pesticides in foods

Modern determination techniques for pesticides must yield identification quickly with high confidence for timely enforcement of tolerances. A protocol for the collection of liquid chromatography (LC) electrospray ionization (ESI)-quadruple linear ion trap (Q-LIT) mass spectrometry (MS) library spectra was developed. Following the protocol, an enhanced product ion (EPI) library of 240 pesticides was developed by use of spectra collected from two laboratories. A LC-Q-LIT-MS workflow using scheduled multiple reaction monitoring (sMRM) survey scan, information-dependent acquisition (IDA) triggered collection of EPI spectra, and library search was developed and tested to identify the 240 target pesticides in one single LC-Q-LIT MS analysis. By use of LC retention time, one sMRM survey scan transition, and a library search, 75-87% of the 240 pesticides were identified in a single LC/MS analysis at fortified concentrations of 10 ng/g in 18 different foods. A conventional approach with LC-MS/MS using two MRM transitions produced the same identifications and comparable quantitative results with the same incurred foods as the LC-Q-LIT using EPI library search, finding 1.2-49 ng/g of either carbaryl, carbendazim, fenbuconazole, propiconazole, or pyridaben in peaches; carbendazim, imazalil, terbutryn, and thiabendazole in oranges; terbutryn in salmon; and azoxystrobin in ginseng. Incurred broccoli, cabbage, and kale were screened with the same EPI library using three LC-Q-LIT and a LC-quadruple time-of-flight (Q-TOF) instruments. The library search identified azoxystrobin, cyprodinil, fludioxinil, imidacloprid, metalaxyl, spinosyn A, D, and J, amd spirotetramat with each instrument. The approach has a broad application in LC-MS/MS type targeted screening in food analysis.     

Characterization of strategies for obtaining confident identifications in bottom-up proteomics measurements using hybrid FTMS instruments

Hybrid FTMS instruments, such as the LTQ-FT and LTQ-Orbitrap, are capable of generating high duty cycle linear ion trap MS/MS data along with high resolution information without compromising the overall throughput of measurements. Combined with online LC separations, these instruments provide powerful capabilities for proteomics research. In the present work, we explore three alternative strategies for high throughput proteomics measurements using hybrid FTMS instruments. Our accurate mass and time tag (AMT tag) strategy enables identification of thousands of peptides in a single LC-FTMS analysis by comparing accurate molecular mass and LC elution time information from the analysis to a reference database. An alternative strategy considered here, termed accurate precursor mass filter (APMF), employs linear ion trap (low resolution) MS/MS identifications generated by an appropriate search engine, such as SEQUEST, refined with high resolution precursor ion data obtained from FTMS mass spectra. The APMF results can be additionally filtered using the LC elution time information from the AMT tag database, which constitutes a precursor mass and time filter (PMTF), the third approach implemented in this study. Both the APMF and the PMTF approaches are evaluated for coverage and confidence of peptide identifications and contrasted with the AMT tag strategy. The commonly used decoy database method and an alternative method based on mass accuracy histograms were used to reliably quantify identification confidence, revealing that both methods yielded similar results. Comparison of the AMT, APMF and PMTF approaches indicates that the AMT tag approach is preferential for studies desiring a highest achievable number of identified peptides. In contrast, the APMF approach does not require an AMT tag database and provides a moderate level of peptide coverage combined with acceptable confidence values of approximately 99%. The PMTF approach yielded a significantly better peptide identification confidence, >99.9%, that essentially excluded any false peptide identifications. Since AMT tag databases that exclude incorrect identifications are desirable, this study points to the value of a multipass APMF approach to generate AMT tag databases, which are then validated using the PMTF approach. The resulting compact, high quality databases can then be used for subsequent high-throughput, high peptide coverage AMT tag studies.     

MALDI analysis of Bacilli in spore mixtures by applying a quadrupole ion trap time-of-flight tandem mass spectrometer

A novel ion trap time-of-flight hybrid mass spectrometer (qIT-TOF MS) has been applied for peptide sequencing in proteolytic digests generated from spore mixtures of Bacilli. The method of on-probe solubilization and in situ proteolytic digestion of small, acid-soluble spore proteins has been recently developed in our laboratory, and microorganism identification in less than 20 min was accomplished. In this study, tryptic peptides were generated in situ from complex spore mixtures of B. subtilis 168, B. globigii, B. thuringiensis subs. Kurstaki, and B. cereus T, respectively. MALDI analysis of bacterial peptides generated was performed with an average mass resolving power of 6200 and a mass accuracy of up to 10 ppm using a trap-TOF tandem configuration. Precursor ions of interest were usually selected and stored in the quadrupole ion trap with their complete isotope distribution by choosing a window of +/- 2 Da. Sequence-specific information on isolated protonated peptides was gained via tandem MS experiments with an average mass resolving power of 4450 for product ion analysis, and protein and bacterial sources were identified by database searching.     

Compound identification using partial and semipartial correlations for gas chromatography-mass spectrometry data

Compound identification is a key component of data analysis in the applications of gas chromatography-mass spectrometry (GC-MS). Currently, the most widely used compound identification is mass spectrum matching, in which the dot product and its composite version are employed as spectral similarity measures. Several forms of transformations for fragment ion intensities have also been proposed to increase the accuracy of compound identification. In this study, we introduced partial and semipartial correlations as mass spectral similarity measures and applied them to identify compounds along with different transformations of peak intensity. The mixture versions of the proposed method were also developed to further improve the accuracy of compound identification. To demonstrate the performance of the proposed spectral similarity measures, the National Institute of Standards and Technology (NIST) mass spectral library and replicate spectral library were used as the reference library and the query spectra, respectively. Identification results showed that the mixture partial and semipartial correlations always outperform both the dot product and its composite measure. The mixture similarity with semipartial correlation has the highest accuracy of 84.6% in compound identification with a transformation of (0.53,1.3) for fragment ion intensity and m/z value, respectively.     

MS for identification of single nucleotide polymorphisms and MS/MS for discrimination of isomeric PCR products

ESI (electrospray ionization) MS and tandem mass spectrometry (MS/MS) were used for the analysis of single nucleotide polymorphisms (SNPs) and more complex genetic variations. Double-stranded (ds) PCR products were studied. PCR products of the proline [5'-x(G17)-x(C38)x-3'] and arginine variants [(5'-x(Gl7)-x(G38)x-3'] of the p53 gene are distinguished by an SNP (cytosine or guanine) and were discriminated using both quadrupole and quadrupole ion trap MS analysis. A 69 bp arginine mutant PCR product [5'-x(C17)-x(G38)x-3'] with a negating switch has the same mass as the proline variant but was readily distinguishable on ion trap MS/MS analysis; fragments containing the mutation site, but not the polymorphism, were identified. The 69 bp PCR products were restriction-enzyme-digested, to create 43 bp fragments. ESI quadrupole ion trap MS/MS analysis of the 43 bp product-ion spectra readily demonstrated both polymorphism and negating switch sites. MS and MS/MS are powerful and complementary techniques for analysis of DNA. MS can readily distinguish SNPs but MS/MS is required to differentiate isomeric PCR products (same nucleotide composition but different sequence).     

MALDI quadrupole time-of-flight mass spectrometry: a powerful tool for proteomic research

A MALDI QqTOF mass spectrometer has been used to identify proteins separated by one-dimensional or two-dimensional gel electrophoresis at the femtomole level. The high mass resolution and the high mass accuracy of this instrument in both MS and MS/MS modes allow identification of a protein either by peptide mass fingerprinting of the protein digest or from tandem mass spectra acquired by collision-induced dissociation of individual peptide precursors. A peptide mass map of the digest and tandem mass spectra of multiple peptide precursor ions can be acquired from the same sample in the course of a single experiment. Database searching and acquisition of MS and MS/MS spectra can be combined in an interactive fashion, increasing the information value of the analytical data. The approach has demonstrated its usefulness in the comprehensive characterization of protein in-gel digests, in the dissection of complex protein mixtures, and in sequencing of a low molecular weight integral membrane protein. Proteins can be identified in all types of sequence databases, including an EST database. Thus, MALDI QqTOF mass spectrometry promises to have remarkable potential for advancing proteomic research.