Database-independent, database-dependent, and extended interpretation of peptide mass spectra in VEMS V2.0

The Virtual Expert Mass Spectrometrist (VEMS) program package was developed for flexible, automated, and manual de novo tandem mass spectrometry (MS/MS) protein sequencing, and includes accessory programs for matrix-assisted laser desorption/ionization-mass spectrometry (MS) interpretation, and generation of protein and peptide databases. VEMS V2.0 has been developed into a fast tool for combining database-independent and -dependent protein assignments in an extended analysis of MS/MS-peptide data. MS or MS/MS data can be directly recalibrated after the first search by fitting the data to the best search result using polynomial equations. The score function is an improvement of known scoring algorithms and can be adapted for any MS instrument type. In addition, VEMS offers a novel statistical model for evaluating the significance of the protein assignment. The novel features are illustrated by the analysis of the fragmentation spectra obtained by liquid chromatrography-MS/MS analysis of peptides from an anionic peroxidase enriched protein fraction from potato root tissue. The extended analysis mode resulted in the additional assignment of spectra for nine modified tryptic peptides and nine miscleaved peptides, in addition to the 45 spectra from regular tryptic peptides. Of the nine modified peptides, three were glycosylated.     

Automated identification of SUMOylation sites using mass spectrometry and SUMmOn pattern recognition software

Tandem mass spectrometry (MS/MS) allows for the rapid identification of many types of post-translational modifications (PTMs), especially those that can be detected by a diagnostic mass shift in one or more peptide fragment ions (for example, phosphorylation). But some PTMs (for example, SUMOs and other ubiquitin-like modifiers) themselves produce multiple fragment ions; combined with fragments from the modified target peptide, a complex overlapping fragmentation pattern is thus generated, which is uninterpretable by standard peptide sequencing software. Here we introduce SUMmOn, an automated pattern recognition tool that detects diagnostic PTM fragment ion series within complex MS/MS spectra, to identify modified peptides and modification sites within these peptides. Using SUMmOn, we demonstrate for the first time that human SUMO-1 multimerizes in vitro primarily via three N-terminal lysines, Lys7, Lys16 and Lys17. Notably, our method is theoretically applicable to any type of modification or chemical moiety generating a unique fragment ion pattern.     

Dynamic spectrum quality assessment and iterative computational analysis of shotgun proteomic data: toward more efficient identification of post-translational modifications, sequence polymorphisms, and novel peptides

In mass spectrometry-based proteomics, frequently hundreds of thousands of MS/MS spectra are collected in a single experiment. Of these, a relatively small fraction is confidently assigned to peptide sequences, whereas the majority of the spectra are not further analyzed. Spectra are not assigned to peptides for diverse reasons. These include deficiencies of the scoring schemes implemented in the database search tools, sequence variations (e.g. single nucleotide polymorphisms) or omissions in the database searched, post-translational or chemical modifications of the peptide analyzed, or the observation of sequences that are not anticipated from the genomic sequence (e.g. splice forms, somatic rearrangement, and processed proteins). To increase the amount of information that can be extracted from proteomic MS/MS datasets we developed a robust method that detects high quality spectra within the fraction of spectra unassigned by conventional sequence database searching and computes a quality score for each spectrum. We also demonstrate that iterative search strategies applied to such detected unassigned high quality spectra significantly increase the number of spectra that can be assigned from datasets and that biologically interesting new insights can be gained from existing data.     

Sequence tag scanning: a new explorative strategy for recognition of unexpected protein alterations by nanoelectrospray ionization-tandem mass spectrometry

Protein analysis by database search engines using tandem mass spectra is limited by the presence of unexpected protein modifications, sequence isoforms which may not be in the protein databases, and poor quality tandem mass spectrometry (MS/MS) of low abundance proteins. The analysis of expected protein modifications can be efficiently addressed by precursor ion scanning. However, it is limited to modifications that show such a characteristic loss in a peptide independent manner. We observed that proline and aspartic acid induced backbone fragmentation is accompanied by a low intensity signal for loss of H3PO4 for several pSer- or pThr-phosphopeptides. We describe here the use of peptide-specific fragments that can be used after a protein was identified to allow in-depth characterization of modifications and isoforms. We consider high abundance fragments formed by cleavage at the C-terminal side of aspartic acid, at the N-terminal side of proline and low mass ions such as a2, b2, b3, y1, y2, and y3. The MS/MS dataset is filtered for each sequence tag of interest by an in silico precursor ion scan. The resulting extracted ion traces are then combined by multiplication to increase specificity. Since the strategy is based on common peptide segments which are shared by different isoforms of peptides it can be applied to the analysis of any post-translational modification or sequence variants of a protein. This is demonstrated for the cases of serine and threonine phosphorylation, histone H1 acetylation and the spotting of multiple H1 isoforms.     

Analysis of the Arabidopsis cytosolic ribosome proteome provides detailed insights into its components and their post-translational modification

Finding gene-specific peptides by mass spectrometry analysis to pinpoint gene loci responsible for particular protein products is a major challenge in proteomics especially in highly conserved gene families in higher eukaryotes. We used a combination of in silico approaches coupled to mass spectrometry analysis to advance the proteomics insight into Arabidopsis cytosolic ribosomal composition and its post-translational modifications. In silico digestion of all 409 ribosomal protein sequences in Arabidopsis defined the proportion of theoretical gene-specific peptides for each gene family and highlighted the need for low m/z cutoffs of MS ion selection for MS/MS to characterize low molecular weight, highly basic ribosomal proteins. We undertook an extensive MS/MS survey of the cytosolic ribosome using trypsin and, when required, chymotrypsin and pepsin. We then used custom software to extract and filter peptide match information from Mascot result files and implement high confidence criteria for calling gene-specific identifications based on the highest quality unambiguous spectra matching exclusively to certain in silico predicted gene- or gene family-specific peptides. This provided an in-depth analysis of the protein composition based on 1446 high quality MS/MS spectra matching to 795 peptide sequences from ribosomal proteins. These identified peptides from five gene families of ribosomal proteins not identified previously, providing experimental data on 79 of the 80 different types of ribosomal subunits. We provide strong evidence for gene-specific identification of 87 different ribosomal proteins from these 79 families. We also provide new information on 30 specific sites of co- and post-translational modification of ribosomal proteins in Arabidopsis by initiator methionine removal, N-terminal acetylation, N-terminal methylation, lysine N-methylation, and phosphorylation. These site-specific modification data provide a wealth of resources for further assessment of the role of ribosome modification in influencing translation in Arabidopsis.     

QuickMod: A tool for open modification spectrum library searches

MS2 library spectra are rich in reproducible information about peptide fragmentation patterns compared to theoretical spectra modeled by a sequence search tool. So far, spectrum library searches are mostly applied to detect peptides as they are present in the library. However, they also allow finding modified variants of the library peptides if the search is done with a large precursor mass window and an adapted Spectrum-Spectrum Match (SSM) scoring algorithm. We perform a thorough evaluation on the use of library spectra as opposed to theoretical peptide spectra for the identification of PTMs, analyzing spectra of a well-annotated modification-rich test data set compiled from public data repositories. These initial studies motivate the development of our modification tolerant spectrum library search tool QuickMod, designed to identify modified variants of the peptides listed in the spectrum library without any prior input from the user estimating the modifications present in the sample. We built the search algorithm of QuickMod after carefully testing different SSM similarity scores. The final spectrum scoring scheme uses a support vector machine (SVM) on a selection of scoring features to classify correct and incorrect SSM. After identification of a list of modified peptides at a given False Discovery Rate (FDR), the modifications need to be positioned on the peptide sequence. We present a rapid modification site assignment algorithm and evaluate its positioning accuracy. Finally, we demonstrate that QuickMod performs favorably in terms of speed and identification rate when compared to other software solutions for PTM analysis.     

A suffix tree approach to the interpretation of tandem mass spectra: applications to peptides of non-specific digestion and post-translational modifications

MOTIVATION: Tandem mass spectrometry combined with sequence database searching is one of the most powerful tools for protein identification. As thousands of spectra are generated by a mass spectrometer in one hour, the speed of database searching is critical, especially when searching against a large sequence database, or when the peptide is generated by some unknown or non-specific enzyme, even or when the target peptides have post-translational modifications (PTM). In practice, about 70-90% of the spectra have no match in the database. Many believe that a significant portion of them are due to peptides of non-specific digestions by unknown enzymes or amino acid modifications. In another case, scientists may choose to use some non-specific enzymes such as pepsin or thermolysin for proteolysis in proteomic study, in that not all proteins are amenable to be digested by some site-specific enzymes, and furthermore many digested peptides may not fall within the rang of molecular weight suitable for mass spectrometry analysis. Interpreting mass spectra of these kinds will cost a lot of computational time of database search engines. OVERVIEW: The present study was designed to speed up the database searching process for both cases. More specifically speaking, we employed an approach combining suffix tree data structure and spectrum graph. The suffix tree is used to preprocess the protein sequence database, while the spectrum graph is used to preprocess the tandem mass spectrum. We then search the suffix tree against the spectrum graph for candidate peptides. We design an efficient algorithm to compute a matching threshold with some statistical significance level, e.g. p = 0.01, for each spectrum, and use it to select candidate peptides. Then we rank these peptides using a SEQUEST-like scoring function. The algorithms were implemented and tested on experimental data. For post-translational modifications, we allow arbitrary number of any modification to a protein. AVAILABILITY: The executable program and other supplementary materials are available online at: http://hto-c.usc.edu:8000/msms/suffix/.     

Simple strategies to enhance discovery of acetylation post-translational modifications by quadrupole-orbitrap LC-MS/MS

Enzyme-dependent post-translational modifications (PTMs) mediate the cellular regulation of proteins and can be discovered using proteomics. However, even where the peptides of interest can be enriched for analysis with state-of-the-art LC-MS/MS tools and informatics, only a fraction of peptide ions can be identified confidently. Thus, many PTM sites remain undiscovered and unconfirmed. In this minireview, we use a case study to discuss how the use of inclusion lists, turning off isotopic exclusion, and manual validation significantly increased depth of coverage, facilitating discovery of acetylation sites in targets of an acetyltransferase virulence factor. These underutilized strategies have the potential to help answer many mechanistic biological questions that large-scale proteomic studies cannot.     

Peptide identification by tandem mass spectrometry with alternate fragmentation modes

The high-throughput nature of proteomics mass spectrometry is enabled by a productive combination of data acquisition protocols and the computational tools used to interpret the resulting spectra. One of the key components in mainstream protocols is the generation of tandem mass (MS/MS) spectra by peptide fragmentation using collision induced dissociation, the approach currently used in the large majority of proteomics experiments to routinely identify hundreds to thousands of proteins from single mass spectrometry runs. Complementary to these, alternative peptide fragmentation methods such as electron capture/transfer dissociation and higher-energy collision dissociation have consistently achieved significant improvements in the identification of certain classes of peptides, proteins, and post-translational modifications. Recognizing these advantages, mass spectrometry instruments now conveniently support fine-tuned methods that automatically alternate between peptide fragmentation modes for either different types of peptides or for acquisition of multiple MS/MS spectra from each peptide. But although these developments have the potential to substantially improve peptide identification, their routine application requires corresponding adjustments to the software tools and procedures used for automated downstream processing. This review discusses the computational implications of alternative and alternate modes of MS/MS peptide fragmentation and addresses some practical aspects of using such protocols for identification of peptides and post-translational modifications.     

The utility of ETD mass spectrometry in proteomic analysis

Mass spectrometry has played an integral role in the identification of proteins and their post-translational modifications (PTM). However, analysis of some PTMs, such as phosphorylation, sulfonation, and glycosylation, is difficult with collision-activated dissociation (CAD) since the modification is labile and preferentially lost over peptide backbone fragmentation, resulting in little to no peptide sequence information. The presence of multiple basic residues also makes peptides exceptionally difficult to sequence by conventional CAD mass spectrometry. Here we review the utility of electron transfer dissociation (ETD) mass spectrometry for sequence analysis of post-translationally modified and/or highly basic peptides. Phosphorylated, sulfonated, glycosylated, nitrosylated, disulfide bonded, methylated, acetylated, and highly basic peptides have been analyzed by CAD and ETD mass spectrometry. CAD fragmentation typically produced spectra showing limited peptide backbone fragmentation. However, when these peptides were fragmented using ETD, peptide backbone fragmentation produced a complete or almost complete series of ions and thus extensive peptide sequence information. In addition, labile PTMs remained intact. These examples illustrate the utility of ETD as an advantageous tool in proteomic research by readily identifying peptides resistant to analysis by CAD. A further benefit is the ability to analyze larger, non-tryptic peptides, allowing for the detection of multiple PTMs within the context of one another.     

N-Terminal amino acid side-chain cleavage of chemically modified peptides in the gas phase: a mass spectrometry technique for N-terminus identification

Although genome databases have become the key for proteomic analyses, de novo sequencing remains essential for the study of organisms whose genomes have not been completed. In addition, post-translational modifications present a challenge in database searching. Recognition of the b or y-ion series in a peptide MS/MS spectrum as well as identification of the b1 - and yn-1 -ions can facilitate de novo analyses. Therefore, it is valuable to identify either amino-acid terminus. In previous work, we have demonstrated that peptides modified at the epsilon-amino group of lysine as a t-butyl peroxycarbamate derivative undergo free radical promoted peptide backbone fragmentation under low-energy collision-induced dissociation (CID) conditions. Here we explore the chemistry of the N-terminal amino group modified as a t-butyl peroxycarbamate. The conversion of N-terminal amines to peroxycarbamates of simple amino acids and peptides was studied with aryl t-butyl peroxycarbonates. ESI-MS/MS analysis of the peroxycarbamate adducts gave evidence of a product ion corresponding to the neutral loss of the N-terminal side chain (R), thus identifying this residue. Further fragmentation (MS3) of product ions formed by N-terminal residue side-chain loss (-R) exhibited an m/z shift of the b-ions equal to the neutral loss of R, therefore labeling the b-ion series. The study was extended to the analysis of a protein tryptic digest where the SALSA algorithm was used to identify spectra containing these neutral losses. The method for N-terminus identification presented here has the potential for improvement of de novo analyses as well as in constraining peptide mass mapping database searches.     

Oxidation of carboxyamidomethyl cysteine may add complexity to protein identification

Protein identification by interrogation of databases requires a comprehensive compilation of modified amino acids forms. Here, we describe the chemical oxidation of carboxyamidomethyl cysteine to the sulfoxide and sulfone forms, species that may add more complexity to peptide analyses. They can be easily distinguished by tandem mass spectrometry (MS/MS) due to their characteristic pattern of side chain neutral eliminations either from the parent ion or ion series that generate dehydroalanine as detected by MS(3). This finding was supported by the MS(n) spectra recorded for a peptide isolated from a mixture of tryptic peptides and for a derivatized/oxidized synthetic peptide with a different sequence. These modifications and their diagnostic neutral losses should be included in the list of chemical modifications and in algorithms designed for the automatic sequencing of peptides and database searching.     

Peptide identification by database search of mixture tandem mass spectra

In high-throughput proteomics the development of computational methods and novel experimental strategies often rely on each other. In certain areas, mass spectrometry methods for data acquisition are ahead of computational methods to interpret the resulting tandem mass spectra. Particularly, although there are numerous situations in which a mixture tandem mass spectrum can contain fragment ions from two or more peptides, nearly all database search tools still make the assumption that each tandem mass spectrum comes from one peptide. Common examples include mixture spectra from co-eluting peptides in complex samples, spectra generated from data-independent acquisition methods, and spectra from peptides with complex post-translational modifications. We propose a new database search tool (MixDB) that is able to identify mixture tandem mass spectra from more than one peptide. We show that peptides can be reliably identified with up to 95% accuracy from mixture spectra while considering only a 0.01% of all possible peptide pairs (four orders of magnitude speedup). Comparison with current database search methods indicates that our approach has better or comparable sensitivity and precision at identifying single-peptide spectra while simultaneously being able to identify 38% more peptides from mixture spectra at significantly higher precision.     

Andromeda: a peptide search engine integrated into the MaxQuant environment

A key step in mass spectrometry (MS)-based proteomics is the identification of peptides in sequence databases by their fragmentation spectra. Here we describe Andromeda, a novel peptide search engine using a probabilistic scoring model. On proteome data, Andromeda performs as well as Mascot, a widely used commercial search engine, as judged by sensitivity and specificity analysis based on target decoy searches. Furthermore, it can handle data with arbitrarily high fragment mass accuracy, is able to assign and score complex patterns of post-translational modifications, such as highly phosphorylated peptides, and accommodates extremely large databases. The algorithms of Andromeda are provided. Andromeda can function independently or as an integrated search engine of the widely used MaxQuant computational proteomics platform and both are freely available at www.maxquant.org. The combination enables analysis of large data sets in a simple analysis workflow on a desktop computer. For searching individual spectra Andromeda is also accessible via a web server. We demonstrate the flexibility of the system by implementing the capability to identify cofragmented peptides, significantly improving the total number of identified peptides.     

Preparative peptide isoelectric focusing as a tool for improving the identification of lysine-acetylated peptides from complex mixtures

Protein sequence database searching of tandem mass spectrometry data is commonly employed to identify post-translational modifications (PTMs) to peptides in global proteomic studies. In these studies, the accurate identification of these modified peptides relies on strategies to ensure high-confidence results from sequence database searching in which differential mass shift parameters are employed to identify PTMs to specific amino acids. Using lysine acetylation as an example PTM, we have observed that the inclusion of differential modification information in sequence database searching dramatically increases the potential for false-positive sequence matches to modified peptides, making the confident identification of true sequence matches difficult. In a proof-of-principle study of whole cell yeast lysates, we demonstrate the combination of preparative isoelectric focusing using free-flow electrophoresis, and an adjusted peptide isoelectric point prediction algorithm, as an effective means to increase the confidence of lysine-acetylated peptide identification. These results demonstrate the potential utility of this general strategy for improving the identification of PTMs which cause a shift to the intrinsic isoelectric point of peptides.     

Peptidomics-based discovery of novel neuropeptides

Modern proteomic methodologies have significantly improved the possibilities of large-scale identification of proteins. However, these methodologies are limited by their inability to reliably detect endogenously expressed peptides. We describe a novel approach of combining sample preparation, comprising focused microwave irradiation and mass spectrometric peptide profiling that has enabled us to simultaneously detect more than 550 endogenous neuropeptides in 1 mg of hypothalamic extracts. Automatic switching tandem mass spectrometry and amino acid sequence determination of the peptides showed that they consist of both novel and previously described neuropeptides. The methodology includes virtual visualization of the peptides as two- and three-dimensional image maps. In addition, several novel and known post-translational modifications of the neuropeptides were identified. The peptidomic approach proved to be a powerful method for investigating endogenous peptides and their post-translational modifications in complex tissues such as the brain. It is anticipated that this approach will complement proteomic methods in the future.     

SeMoP: a new computational strategy for the unrestricted search for modified peptides using LC-MS/MS data

A novel computational approach, termed Search for Modified Peptides (SeMoP), for the unrestricted discovery and verification of peptide modifications in shotgun proteomic experiments using low resolution ion trap MS/MS spectra is presented. Various peptide modifications, including post-translational modifications, sequence polymorphisms, as well as sample handling-induced changes, can be identified using this approach. SeMoP utilizes a three-step strategy: (1) a standard database search to identify proteins in a sample; (2) an unrestricted search for modifications using a newly developed algorithm; and (3) a second standard database search targeted to specific modifications found using the unrestricted search. This targeted approach provides verification of discovered modifications and, due to increased sensitivity, a general increase in the number of peptides with the specific modification. The feasibility of the overall strategy has been first demonstrated in the analysis of 65 plasma proteins. Various sample handling induced modifications, such as beta-elimination of disulfide bridges and pyrocarbamidomethylation, as well as biologically induced modifications, such as phosphorylation and methylation, have been detected. A subsequent targeted Sequest search has been used to verify selected modifications, and a 4-fold increase in the number of modified peptides was obtained. In a second application, 1367 proteins of a cervical cancer cell line were processed, leading to detection of several novel amino acid substitutions. By conducting the search against a database of peptides derived from proteins with decoy sequences, a false discovery rate of less than 5% for the unrestricted search resulted. SeMoP is shown to be an effective and easily implemented approach for the discovery and verification of peptide modifications.     

The spectral networks paradigm in high throughput mass spectrometry

High-throughput proteomics is made possible by a combination of modern mass spectrometry instruments capable of generating many millions of tandem mass (MS(2)) spectra on a daily basis and the increasingly sophisticated associated software for their automated identification. Despite the growing accumulation of collections of identified spectra and the regular generation of MS(2) data from related peptides, the mainstream approach for peptide identification is still the nearly two decades old approach of matching one MS(2) spectrum at a time against a database of protein sequences. Moreover, database search tools overwhelmingly continue to require that users guess in advance a small set of 4-6 post-translational modifications that may be present in their data in order to avoid incurring substantial false positive and negative rates. The spectral networks paradigm for analysis of MS(2) spectra differs from the mainstream database search paradigm in three fundamental ways. First, spectral networks are based on matching spectra against other spectra instead of against protein sequences. Second, spectral networks find spectra from related peptides even before considering their possible identifications. Third, spectral networks determine consensus identifications from sets of spectra from related peptides instead of separately attempting to identify one spectrum at a time. Even though spectral networks algorithms are still in their infancy, they have already delivered the longest and most accurate de novo sequences to date, revealed a new route for the discovery of unexpected post-translational modifications and highly-modified peptides, enabled automated sequencing of cyclic non-ribosomal peptides with unknown amino acids and are now defining a novel approach for mapping the entire molecular output of biological systems that is suitable for analysis with tandem mass spectrometry. Here we review the current state of spectral networks algorithms and discuss possible future directions for automated interpretation of spectra from any class of molecules.