An improved SUMmOn‐based methodology for the identification of ubiquitin and ubiquitin‐like protein conjugation sites identifies novel ubiquitin‐like protein chain linkages

Ubiquitin (Ub) and the ubiquitin‐like proteins (Ubls) comprise a remarkable assortment of polypeptides that are covalently conjugated to target proteins (or other biomolecules) to modulate their intracellular localization, half‐life, and/or activity. Identification of Ub/Ubl conjugation sites on a protein of interest can thus be extremely important for understanding how it is regulated. While MS has become a powerful tool for the study of many classes of PTMs, the identification of Ub/Ubl conjugation sites presents a number of unique challenges. Here, we present an improved Ub/Ubl conjugation site identification strategy, utilizing SUMmOn analysis and an additional protease (lysyl endopeptidase C), as a complement to standard approaches. As compared with standard trypsin proteolysis‐database search protocols alone, the addition of SUMmOn analysis can (i) identify Ubl conjugation sites that are not detected by standard database searching methods, (ii) better preserve Ub/Ubl conjugate identity, and (iii) increase the number of identifications of Ub/Ubl modifications in lysine‐rich protein regions. Using this methodology, we characterize for the first time a number of novel Ubl linkages and conjugation sites, including alternative yeast (K54) and mammalian small ubiquitin‐related modifier (SUMO) chain (SUMO‐2 K42, SUMO‐3 K41) assemblies, as well as previously unreported NEDD8 chain (K27, K33, and K54) topologies.     

XTandem Parser: An open‐source library to parse and analyse X!Tandem MS/MS search results

Identification of proteins by MS plays an important role in proteomics. A crucial step concerns the identification of peptides from MS/MS spectra. The X!Tandem Project ( http://www.thegpm.org/tandem ) supplies an open‐source search engine for this purpose. In this study, we present an open‐source Java library called XTandem Parser that parses X!Tandem XML result files into an easily accessible and fully functional object model ( http://xtandem‐parser.googlecode.com ). In addition, a graphical user interface is provided that functions as a usage example and an end‐user visualization tool.     

Taking it step by step: mechanistic insights from structural studies of ubiquitin/ubiquitin-like protein modification pathways

Ubiquitin (Ub) and ubiquitin-like (Ubl) proteins regulate a diverse array of cellular pathways through post-translational attachment to protein substrates. Ub/Ubl-mediated signaling is initiated through E1, E2, and E3-mediated conjugation, transduced by proteins that recognize Ub/Ubl-modified substrates, and terminated by proteases which remove the Ub/Ubl from the substrate. Recent structural studies have elucidated mechanisms pertinent to Ub/Ubl conjugation, recognition, and deconjugation, highlighting essential steps during Ub/Ubl modification that illustrate common and divergent mechanistic themes within this important process.     

HMMatch: peptide identification by spectral matching of tandem mass spectra using hidden Markov models.

Peptide identification by tandem mass spectrometry is the dominant proteomics workflow for protein characterization in complex samples. The peptide fragmentation spectra generated by these workflows exhibit characteristic fragmentation patterns that can be used to identify the peptide. In other fields, where the compounds of interest do not have the convenient linear structure of peptides, fragmentation spectra are identified by comparing new spectra with libraries of identified spectra, an approach called spectral matching. In contrast to sequence-based tandem mass spectrometry search engines used for peptides, spectral matching can make use of the intensities of fragment peaks in library spectra to assess the quality of a match. We evaluate a hidden Markov model approach (HMMatch) to spectral matching, in which many examples of a peptide's fragmentation spectrum are summarized in a generative probabilistic model that captures the consensus and variation of each peak's intensity. We demonstrate that HMMatch has good specificity and superior sensitivity, compared to sequence database search engines such as X!Tandem. HMMatch achieves good results from relatively few training spectra, is fast to train, and can evaluate many spectra per second. A statistical significance model permits HMMatch scores to be compared with each other, and with other peptide identification tools, on a unified scale. HMMatch shows a similar degree of concordance with X!Tandem, Mascot, and NIST's MS Search, as they do with each other, suggesting that each tool can assign peptides to spectra that the others miss. Finally, we show that it is possible to extrapolate HMMatch models beyond a single peptide's training spectra to the spectra of related peptides, expanding the application of spectral matching techniques beyond the set of peptides previously observed.     

A bioluminescent assay for monitoring conjugation of ubiquitin and ubiquitin-like proteins

Post-translational modification of target proteins by ubiquitin (Ub) and ubiquitin-like (Ubl) proteins is a critical mechanism for regulating protein functions affecting diverse cellular processes. Ub/Ubl proteins are conjugated to lysine residues in substrate proteins through an adenosine triphosphate (ATP)-dependent enzymatic cascade involving enzyme 1 (E1)-activating enzyme, E2-conjugating enzyme, and E3 ligase. The amount of adenosine monophosphate (AMP) produced in the first step, involving E1-mediated Ub/Ubl activation, represents an accurate measure of Ub/Ubl transfer during the process. Here we describe a novel bioluminescent assay platform, AMP-Glo, to quantify Ub/Ubl conjugation by measuring the AMP generated. The AMP-Glo assay is performed in a two-step reaction. The first step terminates the ubiquitination reaction, depletes the remaining ATP, and converts the AMP generated in the ubiquitination reaction to adenosine diphosphate (ADP), and in the second step the ADP generated is converted to ATP, which is detected as a bioluminescent signal using luciferase/luciferin, proportional to the AMP concentration and correlated with the Ub/Ubl transfer activity. We demonstrate the use of the assay to study Ub/Ubl conjugation and screen for chemical modulators of enzymes involved in the process. Because there is a sequential enhancement in light output in the presence of E1, E2, and E3, the AMP-Glo system can be used to deconvolute inhibitor specificity.     

An evaluation, comparison, and accurate benchmarking of several publicly available MS/MS search algorithms: sensitivity and specificity analysis

MS/MS and associated database search algorithms are essential proteomic tools for identifying peptides. Due to their widespread use, it is now time to perform a systematic analysis of the various algorithms currently in use. Using blood specimens used in the HUPO Plasma Proteome Project, we have evaluated five search algorithms with respect to their sensitivity and specificity, and have also accurately benchmarked them based on specified false-positive (FP) rates. Spectrum Mill and SEQUEST performed well in terms of sensitivity, but were inferior to MASCOT, X!Tandem, and Sonar in terms of specificity. Overall, MASCOT, a probabilistic search algorithm, correctly identified most peptides based on a specified FP rate. The rescoring algorithm, PeptideProphet, enhanced the overall performance of the SEQUEST algorithm, as well as provided predictable FP error rates. Ideally, score thresholds should be calculated for each peptide spectrum or minimally, derived from a reversed-sequence search as demonstrated in this study based on a validated data set. The availability of open-source search algorithms, such as X!Tandem, makes it feasible to further improve the validation process (manual or automatic) on the basis of "consensus scoring", i.e., the use of multiple (at least two) search algorithms to reduce the number of FPs. complement.     

Proteomic identification of ubiquitinated proteins from human cells expressing His-tagged ubiquitin

A proteomics method has been developed to purify and identify the specific proteins modified by ubiquitin (Ub) from human cells. In purified samples, Ub and 21 other proteins were identified by liquid chromatography-tandem mass spectrometry (LC-MS/MS) spectra using SEQUEST. These proteins included several of the expected carriers of Ub including Ub-conjugating enzymes and histone proteins. To perform these experiments, a cell line coexpressing epitope tagged His(6X)-Ub and green fluorescent protein (GFP) was generated by stably transfecting HEK293 cells. Ubiquitinated proteins were purified using nickel-affinity chromatography and digested in solution with trypsin. Complex mixtures of peptides were separated by reversed phase chromatography and analyzed by nano LC-MS/MS using the LCQ quadrupole ion-trap mass spectrometer. Proteins identified from His(6X)-Ub-GFP transfected cells were compared to a list of proteins from HEK293 cells, which associate with nickel-nitrilotriacetic acid (Ni-NTA)-agarose in the absence of His-tagged Ub. In a proof of principle experiment, His(6X)-Ub-GFP transfected cells were treated with As (III) (10 microM, 24 h) in an attempt to identify substrates increasingly modified by Ub. In this experiment, proliferating cell nuclear antigen, a DNA repair protein and known ubiquitin substrate, was confidently identified. This proteomics method, developed for the analysis of ubiquitinated proteins, is a step towards large-scale characterization of Ub-protein conjugates in numerous physiological and pathological states.     

Interplay between poxviruses and the cellular ubiquitin/ubiquitin-like pathways

Post-translational polypeptide tagging by conjugation with ubiquitin and ubiquitin-like (Ub/Ubl) molecules is a potent way to alter protein functions and/or sort specific protein targets to the proteasome for degradation. Many poxviruses interfere with the host Ub/Ubl system by encoding viral proteins that can usurp this pathway. Some of these include viral proteins of the membrane-associated RING-CH (MARCH) domain, p28/Really Interesting New Gene (RING) finger, ankyrin-repeat/F-box and Broad-complex, Tramtrack and Bric-a-Brac (BTB)/Kelch subgroups of the E3 Ub ligase superfamily. Here we describe and discuss the various strategies used by poxviruses to target and subvert the host cell Ub/Ubl systems.     

LFQuant: A label‐free fast quantitative analysis tool for high‐resolution LC‐MS/MS proteomics data

Database searching based methods for label‐free quantification aim to reconstruct the peptide extracted ion chromatogram based on the identification information, which can limit the search space and thus make the data processing much faster. The random effect of the MS/MS sampling can be remedied by cross‐assignment among different runs. Here, we present a new label‐free fast quantitative analysis tool, LFQuant, for high‐resolution LC‐MS/MS proteomics data based on database searching. It is designed to accept raw data in two common formats (mzXML and Thermo RAW), and database search results from mainstream tools (MASCOT, SEQUEST, and X!Tandem), as input data. LFQuant can handle large‐scale label‐free data with fractionation such as SDS‐PAGE and 2D LC. It is easy to use and provides handy user interfaces for data loading, parameter setting, quantitative analysis, and quantitative data visualization. LFQuant was compared with two common quantification software packages, MaxQuant and IDEAL‐Q, on the replication data set and the UPS1 standard data set. The results show that LFQuant performs better than them in terms of both precision and accuracy, and consumes significantly less processing time. LFQuant is freely available under the GNU General Public License v3.0 at http://sourceforge.net/projects/lfquant/ .     

A bioinformatics workflow for variant peptide detection in shotgun proteomics

Shotgun proteomics data analysis usually relies on database search. However, commonly used protein sequence databases do not contain information on protein variants and thus prevent variant peptides and proteins from been identified. Including known coding variations into protein sequence databases could help alleviate this problem. Based on our recently published human Cancer Proteome Variation Database, we have created a protein sequence database that comprehensively annotates thousands of cancer-related coding variants collected in the Cancer Proteome Variation Database as well as noncancer-specific ones from the Single Nucleotide Polymorphism Database (dbSNP). Using this database, we then developed a data analysis workflow for variant peptide identification in shotgun proteomics. The high risk of false positive variant identifications was addressed by a modified false discovery rate estimation method. Analysis of colorectal cancer cell lines SW480, RKO, and HCT-116 revealed a total of 81 peptides that contain either noncancer-specific or cancer-related variations. Twenty-three out of 26 variants randomly selected from the 81 were confirmed by genomic sequencing. We further applied the workflow on data sets from three individual colorectal tumor specimens. A total of 204 distinct variant peptides were detected, and five carried known cancer-related mutations. Each individual showed a specific pattern of cancer-related mutations, suggesting potential use of this type of information for personalized medicine. Compatibility of the workflow has been tested with four popular database search engines including Sequest, Mascot, X!Tandem, and MyriMatch. In summary, we have developed a workflow that effectively uses existing genomic data to enable variant peptide detection in proteomics.     

MassMatrix: A database search program for rapid characterization of proteins and peptides from tandem mass spectrometry data

MassMatrix is a program that matches tandem mass spectra with theoretical peptide sequences derived from a protein database. The program uses a mass accuracy sensitive probabilistic score model to rank peptide matches. The MS/MS search software was evaluated by use of a high mass accuracy dataset and its results compared with those from MASCOT, SEQUEST, X!Tandem, and OMSSA. For the high mass accuracy data, MassMatrix provided better sensitivity than MASCOT, SEQUEST, X!Tandem, and OMSSA for a given specificity and the percentage of false positives was 2%. More importantly all manually validated true positives corresponded to a unique peptide/spectrum match. The presence of decoy sequence and additional variable PTMs did not significantly affect the results from the high mass accuracy search. MassMatrix performs well when compared with MASCOT, SEQUEST, X!Tandem, and OMSSA with regard to search time. MassMatrix was also run on a distributed memory clusters and achieved search speeds of ～100 000 spectra per hour when searching against a complete human database with eight variable modifications. The algorithm is available for public searches at http://www.massmatrix.net.     

PeaksPTM: Mass spectrometry-based identification of peptides with unspecified modifications

Tandem mass spectrometry (MS/MS) has been routinely used to identify peptides from a protein sequence database. To identify post-translationally modified peptides, most existing software requires the specification of a few possible modifications. However, such knowledge of possible modifications is not always available. In this paper, we describe a new algorithm for identifying modified peptides without requiring the user to specify the possible modifications; instead, all modifications from the Unimod database are considered. Meanwhile, several new techniques are employed to avoid the exponential growth of the search space, as well as to control the false discoveries due to this unrestricted search approach. Finally, a software tool, PeaksPTM, has been developed and already achieved a stronger performance than competitive tools for unrestricted identification of post-translational modifications.     

Ubiquitin and ubiquitin-like specific proteases targeted by infectious pathogens: Emerging patterns and molecular principles

Attachment of ubiquitin (Ub) or ubiquitin-like (Ubl) modifiers is a reversible post-translational modification that regulates the fate and function of proteins. In particular, proteolytic enzymes with Ub/Ubl processing activity appear to be more widespread than originally anticipated. It is therefore not surprising that bacterial and viral pathogens have exploited many ways to interfere with Ub/Ubl conjugation, but also de-conjugation. On one hand, pathogens were shown to manipulate host encoded enzymes. On the other hand, pathogen derived sequences of proteases specific for Ub/Ubls are emerging as a common feature shared by many viruses, bacteria and protozoa, and we are at an early stage of understanding how these proteases contribute to the pathogenesis of infection. Whereas some of these proteases share a common origin with mammalian cell encoded hydrolases with specific properties towards Ub/Ubls, most of them have ancient intrinsic functions, such as processing pathogen protein components, and may have acquired the specificity for Ub/Ubls by interacting with mammalian hosts and their immune system throughout evolution. Since many of these proteases are clearly distinct from their mammalian counterparts, they represent attractive targets for drug design against infectious diseases.     

Integrated platform for manual and high‐throughput statistical validation of tandem mass spectra

As proteomic data sets increase in size and complexity, the necessity for database‐centric software systems able to organize, compare, and visualize all the proteomic experiments in a lab grows. We recently developed an integrated platform called high‐throughput autonomous proteomic pipeline (HTAPP) for the automated acquisition and processing of quantitative proteomic data, and integration of proteomic results with existing external protein information resources within a lab‐based relational database called PeptideDepot. Here, we introduce the peptide validation software component of this system, which combines relational database‐integrated electronic manual spectral annotation in Java with a new software tool in the R programming language for the generation of logistic regression spectral models from user‐supplied validated data sets and flexible application of these user‐generated models in automated proteomic workflows. This logistic regression spectral model uses both variables computed directly from SEQUEST output in addition to deterministic variables based on expert manual validation criteria of spectral quality. In the case of linear quadrupole ion trap (LTQ) or LTQ‐FTICR LC/MS data, our logistic spectral model outperformed both XCorr (242% more peptides identified on average) and the X!Tandem E‐value (87% more peptides identified on average) at a 1% false discovery rate estimated by decoy database approach.     

Expanding the ubiquitin code through post‐translational modification

Ubiquitylation is among the most prevalent post‐translational modifications (PTMs) and regulates numerous cellular functions. Interestingly, ubiquitin (Ub) can be itself modified by other PTMs, including acetylation and phosphorylation. Acetylation of Ub on K6 and K48 represses the formation and elongation of Ub chains. Phosphorylation of Ub happens on multiple sites, S57 and S65 being the most frequently modified in yeast and mammalian cells, respectively. In mammals, the PINK1 kinase activates ubiquitin ligase Parkin by phosphorylating S65 of Ub and of the Parkin Ubl domain, which in turn promotes the amplification of autophagy signals necessary for the removal of damaged mitochondria. Similarly, TBK1 phosphorylates the autophagy receptors OPTN and p62 to initiate feedback and feedforward programs for Ub‐dependent removal of protein aggregates, mitochondria and pathogens (such as Salmonella and Mycobacterium tuberculosis). The impact of PINK1‐mediated phosphorylation of Ub and TBK1‐dependent phosphorylation of autophagy receptors (OPTN and p62) has been recently linked to the development of Parkinson's disease and amyotrophic lateral sclerosis, respectively. Hence, the post‐translational modification of Ub and its receptors can efficiently expand the Ub code and modulate its functions in health and disease.     

Clustering millions of tandem mass spectra

Tandem mass spectrometry (MS/MS) experiments often generate redundant data sets containing multiple spectra of the same peptides. Clustering of MS/MS spectra takes advantage of this redundancy by identifying multiple spectra of the same peptide and replacing them with a single representative spectrum. Analyzing only representative spectra results in significant speed-up of MS/MS database searches. We present an efficient clustering approach for analyzing large MS/MS data sets (over 10 million spectra) with a capability to reduce the number of spectra submitted to further analysis by an order of magnitude. The MS/MS database search of clustered spectra results in fewer spurious hits to the database and increases number of peptide identifications as compared to regular nonclustered searches. Our open source software MS-Clustering is available for download at http://peptide.ucsd.edu or can be run online at http://proteomics.bioprojects.org/MassSpec.     

General framework for developing and evaluating database scoring algorithms using the TANDEM search engine

MOTIVATION: Tandem mass spectrometry (MS/MS) identifies protein sequences using database search engines, at the core of which is a score that measures the similarity between peptide MS/MS spectra and a protein sequence database. The TANDEM application was developed as a freely available database search engine for the proteomics research community. To extend TANDEM as a platform for further research on developing improved database scoring methods, we modified the software to allow users to redefine the scoring function and replace the native TANDEM scoring function while leaving the remaining core application intact. Redefinition is performed at run time so multiple scoring functions are available to be selected and applied from a single search engine binary. We introduce the implementation of the pluggable scoring algorithm and also provide implementations of two TANDEM compatible scoring functions, one previously described scoring function compatible with PeptideProphet and one very simple scoring function that quantitative researchers may use to begin their development. This extension builds on the open-source TANDEM project and will facilitate research into and dissemination of novel algorithms for matching MS/MS spectra to peptide sequences. The pluggable scoring schema is also compatible with related search applications P3 and Hunter, which are part of the X! suite of database matching algorithms. The pluggable scores and the X! suite of applications are all written in C++. AVAILABILITY: Source code for the scoring functions is available from http://proteomics.fhcrc.org     

SQID: an intensity-incorporated protein identification algorithm for tandem mass spectrometry

To interpret LC-MS/MS data in proteomics, most popular protein identification algorithms primarily use predicted fragment m/z values to assign peptide sequences to fragmentation spectra. The intensity information is often undervalued, because it is not as easy to predict and incorporate into algorithms. Nevertheless, the use of intensity to assist peptide identification is an attractive prospect and can potentially improve the confidence of matches and generate more identifications. On the basis of our previously reported study of fragmentation intensity patterns, we developed a protein identification algorithm, SeQuence IDentfication (SQID), that makes use of the coarse intensity from a statistical analysis. The scoring scheme was validated by comparing with Sequest and X!Tandem using three data sets, and the results indicate an improvement in the number of identified peptides, including unique peptides that are not identified by Sequest or X!Tandem. The software and source code are available under the GNU GPL license at http://quiz2.chem.arizona.edu/wysocki/bioinformatics.htm.