Refining spectral library searching

Spectral library searching has many advantages over sequence database searching, yet it has not been widely adopted. One possible reason for this is that users are unsure exactly how to interpret the similarity scores (e.g., “dot products” are not probability‐based scores). Methods to create decoys have been proposed, but, as developers caution, may produce proxies that are not equivalent to reversed sequences. In this issue, Shao et al. (Proteomics 2013, 13, 3273–3283) report advances in spectral library searching where the focus is not on improving the performance of their search engine, SpectraST, but is instead on improving the statistical meaningfulness of its discriminant score and removing the need for decoys. The results in their paper indicate that by “standardizing” the input and library spectra, sensitivity is not lost but is, surprisingly, gained. Their tests also show that false discovery rate (FDR) estimates, derived from their new score, track better with “ground truth” than decoy searching. It is possible that their work strikes a good balance between the theory of library searching and its application. And as such, they hope to have removed a major entrance barrier for some researchers previously unwilling to try library searching.     

Building and searching tandem mass (MS/MS) spectral libraries for peptide identification in proteomics

Spectral library searching is an emerging approach in peptide identifications from tandem mass spectra, a critical step in proteomic data analysis. In spectral library searching, a spectral library is first meticulously compiled from a large collection of previously observed peptide MS/MS spectra that are conclusively assigned to their corresponding amino acid sequence. An unknown spectrum is then identified by comparing it to all the candidates in the spectral library for the most similar match. This review discusses the basic principles of spectral library building and searching, describes its advantages and limitations, and provides a primer for researchers interested in adopting this new approach in their data analysis. It will also discuss the future outlook on the evolution and utility of spectral libraries in the field of proteomics.     

Refining similarity scoring to enable decoy‐free validation in spectral library searching

Spectral library searching is a maturing approach for peptide identification from MS/MS, offering an alternative to traditional sequence database searching. Spectral library searching relies on direct spectrum‐to‐spectrum matching between the query data and the spectral library, which affords better discrimination of true and false matches, leading to improved sensitivity. However, due to the inherent diversity of the peak location and intensity profiles of real spectra, the resulting similarity score distributions often take on unpredictable shapes. This makes it difficult to model the scores of the false matches accurately, necessitating the use of decoy searching to sample the score distribution of the false matches. Here, we refined the similarity scoring in spectral library searching to enable the validation of spectral search results without the use of decoys. We rank‐transformed the peak intensities to standardize all spectra, making it possible to fit a parametric distribution to the scores of the nontop‐scoring spectral matches. The statistical significance of the top‐scoring match can then be estimated in a rigorous manner according to Extreme Value Theory. The overall result is a more robust and interpretable measure of the quality of the spectral match, which can be obtained without decoys. We tested this refined similarity scoring function on real datasets and demonstrated its effectiveness. This approach reduces search time, increases sensitivity, and extends spectral library searching to situations where decoy spectra cannot be readily generated, such as in searching unidentified and nonpeptide spectral libraries.     

Protein and peptide identification algorithms using MS for use in high-throughput, automated pipelines

Current proteomics experiments can generate vast quantities of data very quickly, but this has not been matched by data analysis capabilities. Although there have been a number of recent reviews covering various aspects of peptide and protein identification methods using MS, comparisons of which methods are either the most appropriate for, or the most effective at, their proposed tasks are not readily available. As the need for high-throughput, automated peptide and protein identification systems increases, the creators of such pipelines need to be able to choose algorithms that are going to perform well both in terms of accuracy and computational efficiency. This article therefore provides a review of the currently available core algorithms for PMF, database searching using MS/MS, sequence tag searches and de novo sequencing. We also assess the relative performances of a number of these algorithms. As there is limited reporting of such information in the literature, we conclude that there is a need for the adoption of a system of standardised reporting on the performance of new peptide and protein identification algorithms, based upon freely available datasets. We go on to present our initial suggestions for the format and content of these datasets.     

A simple workflow to increase MS2 identification rate by subsequent spectral library search

Searching a spectral library for the identification of protein MS/MS data has proven to be a fast and accurate method, while yielding a high identification rate. We investigated the potential to increase peptide discovery rate, with little increase in computational time, by constructing a workflow based on a sequence search with Phenyx followed by a library search with SpectraST. Searching a consensus library compiled from the search results of the prior Phenyx search increased the number of confidently matched spectra by up to 156%. Additionally matched spectra by SpectraST included noisy spectra, spectra representing missed cleaved peptides as well as spectra from post‐translationally modified peptides.     

A semi-empirical approach for predicting unobserved peptide MS/MS spectra from spectral libraries

Spectral library searching is a promising alternative to sequence database searching in peptide identification from MS/MS spectra. The key advantage of spectral library searching is the utilization of more spectral features to improve score discrimination between good and bad matches, and hence sensitivity. However, the coverage of reference spectral library is limited by current experimental and computational methods. We developed a computational approach to expand the coverage of spectral libraries with semi-empirical spectra predicted from perturbing known spectra of similar sequences, such as those with single amino acid substitutions. We hypothesized that the peptide of similar sequences should produce similar fragmentation patterns, at least in most cases. Our results confirm our hypothesis and specify when this approach can be applied. In actual spectral searching of real data sets, the sensitivity advantage of spectral library searching over sequence database searching can be mostly retained even when all real spectra are replaced by semi-empirical ones. We demonstrated the applicability of this approach by detecting several known non-synonymous single-nucleotide polymorphisms in three large human data sets by spectral searching.     

IPeak: An open source tool to combine results from multiple MS/MS search engines

Liquid chromatography coupled tandem mass spectrometry (LC‐MS/MS) is an important technique for detecting peptides in proteomics studies. Here, we present an open source software tool, termed IPeak, a peptide identification pipeline that is designed to combine the Percolator post‐processing algorithm and multi‐search strategy to enhance the sensitivity of peptide identifications without compromising accuracy. IPeak provides a graphical user interface (GUI) as well as a command‐line interface, which is implemented in JAVA and can work on all three major operating system platforms: Windows, Linux/Unix and OS X. IPeak has been designed to work with the mzIdentML standard from the Proteomics Standards Initiative (PSI) as an input and output, and also been fully integrated into the associated mzidLibrary project, providing access to the overall pipeline, as well as modules for calling Percolator on individual search engine result files. The integration thus enables IPeak (and Percolator) to be used in conjunction with any software packages implementing the mzIdentML data standard. IPeak is freely available and can be downloaded under an Apache 2.0 license at https://code.google.com/p/mzidentml‐lib/ .     

STEPS: A grid search methodology for optimized peptide identification filtering of MS/MS database search results

For bottom‐up proteomics, there are wide variety of database‐searching algorithms in use for matching peptide sequences to tandem MS spectra. Likewise, there are numerous strategies being employed to produce a confident list of peptide identifications from the different search algorithm outputs. Here we introduce a grid‐search approach for determining optimal database filtering criteria in shotgun proteomics data analyses that is easily adaptable to any search. Systematic Trial and Error Parameter Selection‐–referred to as STEPS‐–utilizes user‐defined parameter ranges to test a wide array of parameter combinations to arrive at an optimal “parameter set” for data filtering, thus maximizing confident identifications. The benefits of this approach in terms of numbers of true‐positive identifications are demonstrated using datasets derived from immunoaffinity‐depleted blood serum and a bacterial cell lysate, two common proteomics sample types.     

Development of a herbicide biosensor using a peptide receptor screened from a combinatorial library

The purpose of this study was to screen for peptides that bind herbicides with a chlorinated aniline chemical structure. A tetrapeptide library was constructed using a solid phase split synthesis approach. Peptide beads were suspended in a buffer containing fluorescent-labeled dichloroaniline (DCA) as the bait. Eighteen fluorescent peptide beads were selected which bound to the bait after two rounds of staining screenings. The beads were then stained and suspended in a solution containing an excess of DCA and five quenched peptide beads were subsequently selected that recognized the DCA moiety. The screened peptides had many sequence similarities. The binding affinity of the screened peptides to herbicides was analyzed using surface plasmon resonance (SPR). N′-(3,4-dichlorophenyl)-N,N-dimethylurea [3-(3,4-dichlorophenyl)-1,1-dimethylurea] solution was injected over the peptide immobilized SPR chip. The SPR signal was found to increase in proportion to the DCMU concentration, whereas no signal was obtained from the negative control, 2-(2-methyl-4-chlorophenoxy) propionic acid (MCPP). From these results it is suggested that the screened peptide selectively recognizes the chemical structure of DCA.     

MassSieve: Panning MS/MS peptide data for proteins

We present MassSieve, a Java‐based platform for visualization and parsimony analysis of single and comparative LC‐MS/MS database search engine results. The success of mass spectrometric peptide sequence assignment algorithms has led to the need for a tool to merge and evaluate the increasing data set sizes that result from LC‐MS/MS‐based shotgun proteomic experiments. MassSieve supports reports from multiple search engines with differing search characteristics, which can increase peptide sequence coverage and/or identify conflicting or ambiguous spectral assignments.     

An enhanced method for peptides sequencing by N-terminal derivatization and MS

An improved method for peptide sequencing based on acetylation/deuteroacetylation in conjunction with ESI MS is introduced. Derivatization with a 1:1 mixture of acetic anhydride and deuterated acetic anhydride incorporates a stable isotope label into the analyzed molecule. This approach has been initially applied to FAB. Using MS/MS, the technique provides a fast, highly sensitive and reliable determination of the primary structure of unknown peptides. This procedure labels N-terminal fragments formed during MS/MS analysis, resulting in a simplification and faster interpretation of the spectra. The performance of the method has been tested with several synthetic peptides and applied to an efficient sequencing of the peptide map, using a nano-scale LC coupled on-line to a tandem mass spectrometer.     

pepgrep: A Tool for Peptide MS/MS Pattern Matching

Typically, detection of protein sequences in collision-induced dissociation (CID) tandem MS (MS2) dataset is performed by mapping identified peptide ions back to protein sequence by using the protein database search (PDS) engine. Finding a particular peptide sequence of interest in CID MS2 records very often requires manual evaluation of the spectrum, regardless of whether the peptide-associated MS2 scan is identified by PDS algorithm or not. We have developed a compact cross-platform database-free command-line utility, pepgrep, which helps to find an MS2 fingerprint for a selected peptide sequence by pattern-matching of modelled MS2 data using Peptide-to-MS2 scoring algorithm. pepgrep can incorporate dozens of mass offsets corresponding to a variety of post-translational modifications (PTMs) into the algorithm. Decoy peptide sequences are used with the tested peptide sequence to reduce false-positive results. The engine is capable of screening an MS2 data file at a high rate when using a cluster computing environment. The matched MS2 spectrum can be displayed by using built-in graphical application programming interface (API) or optionally recorded to file. Using this algorithm, we were able to find extra peptide sequences in studied CID spectra that were missed by PDS identification. Also we found pepgrep especially useful for examining a CID of small fractions of peptides resulting from, for example, affinity purification techniques. The peptide sequences in such samples are less likely to be positively identified by using routine protein-centric algorithm implemented in PDS. The software is freely available at http://bsproteomics.essex.ac.uk:8080/data/download/pepgrep-1.4.tgz.     

A broad-spectrum fluorescence-based peptide library for the rapid identification of protease substrates

Identification of peptide substrates for proteases can be a major undertaking. To overcome issues such as feasibility and deconvolution, associated with large peptide libraries, a 'small but smart' generic fluorescence resonance energy transfer rapid endopeptidase profiling library (REPLi) was synthesised as a tool for rapidly identifying protease substrates. Within a tripeptide core, flanked by Gly residues, similar amino acids were paired giving rise to a relatively small library of 3375 peptides divided into 512 distinct pools each containing only 8 peptides. The REPLi was validated with trypsin, pepsin, the matrix metalloprotease (MMP)-12 and MMP-13 and calpains-1 and -2. In the case of calpain-2, a single iteration step involving LC-MS, provided the definitive residue specificity from which a highly sensitive fluorogenic substrate, (FAM)-Gly-Gly-Gly-Gln-Leu-Tyr-Gly-Gly-DPA-Arg-Arg-Lys-(TAMRA), was then designed. The thorough validation of this 'small but smart' peptide library with representatives from each of the four mechanistic protease classes indicates that the REPLi will be useful for the rapid identification of substrates for multiple proteases.     

The NISTmAb tryptic peptide spectral library for monoclonal antibody characterization

We describe the creation of a mass spectral library composed of all identifiable spectra derived from the tryptic digest of the NISTmAb IgG1κ. The library is a unique reference spectral collection developed from over six million peptide-spectrum matches acquired by liquid chromatography-mass spectrometry (LC-MS) over a wide range of collision energy. Conventional one-dimensional (1D) LC-MS was used for various digestion conditions and 20- and 24-fraction two-dimensional (2D) LC-MS studies permitted in-depth analyses of single digests. Computer methods were developed for automated analysis of LC-MS isotopic clusters to determine the attributes for all ions detected in the 1D and 2D studies. The library contains a selection of over 12,600 high-quality tandem spectra of more than 3,300 peptide ions identified and validated by accurate mass, differential elution pattern, and expected peptide classes in peptide map experiments. These include a variety of biologically modified peptide spectra involving glycosylated, oxidized, deamidated, glycated, and N/C-terminal modified peptides, as well as artifacts. A complete glycation profile was obtained for the NISTmAb with spectra for 58% and 100% of all possible glycation sites in the heavy and light chains, respectively. The site-specific quantification of methionine oxidation in the protein is described. The utility of this reference library is demonstrated by the analysis of a commercial monoclonal antibody (adalimumab, Humira®), where 691 peptide ion spectra are identifiable in the constant regions, accounting for 60% coverage for both heavy and light chains. The NIST reference library platform may be used as a tool for facile identification of the primary sequence and post-translational modifications, as well as the recognition of LC-MS method-induced artifacts for human and recombinant IgG antibodies. Its development also provides a general method for creating comprehensive peptide libraries of individual proteins.     

A comparison of nLC-ESI-MS/MS and nLC-MALDI-MS/MS for GeLC-based protein identification and iTRAQ-based shotgun quantitative proteomics.

The use of nLC-ESI-MS/MS in shotgun proteomics experiments and GeLC-MS/MS analysis is well accepted and routinely available in most proteomics laboratories. However, the same cannot be said for nLC-MALDI MS/MS, which has yet to experience such widespread acceptance, despite the fact that the MALDI technology offers several critical advantages over ESI. As an illustration, in an analysis of moderately complex sample of E. coli proteins, the use MALDI in addition to ESI in GeLC-MS/MS resulted in a 16% average increase in protein identifications, while with more complex samples the number of additional protein identifications increased by an average of 45%. The size of the unique peptides identified by MALDI was, on average, 25% larger than the unique peptides identified by ESI, and they were found to be slightly more hydrophilic. The insensitivity of MALDI to the presence of ionization suppression agents was shown to be a significant advantage, suggesting it be used as a complement to ESI when ion suppression is a possibility. Furthermore, the higher resolution of the TOF/TOF instrument improved the sensitivity, accuracy, and precision of the data over that obtained using only ESI-based iTRAQ experiments using a linear ion trap. Nevertheless, accurate data can be generated with either instrument. These results demonstrate that coupling nanoLC with both ESI and MALDI ionization interfaces improves proteome coverage, reduces the deleterious effects of ionization suppression agents, and improves quantitation, particularly in complex samples.     

Antibody-based enrichment of peptides on magnetic beads for mass-spectrometry-based quantification of serum biomarkers

A major bottleneck for validation of new clinical diagnostics is the development of highly sensitive and specific assays for quantifying proteins. We previously described a method, stable isotope standards with capture by antipeptide antibodies, wherein a specific tryptic peptide is selected as a stoichiometric representative of the protein from which it is cleaved, is enriched from biological samples using immobilized antibodies, and is quantitated using mass spectrometry against a spiked internal standard to yield a measure of protein concentration. In this study, we optimized a magnetic-bead-based platform amenable to high-throughput peptide capture and demonstrated that antibody capture followed by mass spectrometry can achieve ion signal enhancements on the order of 10(3), with precision (CVs <10%) and accuracy (relative error approximately 20%) sufficient for quantifying biomarkers in the physiologically relevant ng/mL range. These methods are generally applicable to any protein or biological fluid of interest and hold great potential for providing a desperately needed bridging technology between biomarker discovery and clinical application.     

Development and validation of an LC-MS/MS method for determination of 8-iso-prostaglandin f2 Alpha in human saliva

BackgroundIncreased formation of reactive oxygen species may be caused by the ion release of the metal alloys used in prosthetic dental restorations due to the corrosion process. As products of lipid peroxidation, isoprostanes can be used as a marker for oxidative stress in the body. There are two significant advantages of using isoprostanes as an oxidative stress marker - presence in all fluids in the body and low reactivity. Saliva provides noninvasive, painless, and cost-effective sample collection and can be used as an alternative testing medium of blood and urine.MethodsThis study presents the development and validation of a sample LC-MS/MS method to quantify 8-isoprostaglandin F2-a in human saliva using salt-out assisted liquid-liquid extraction (SALLE).ResultsThe selected sample preparation procedure optimized chromatographic separation and mass detection provided high recovery and sensitivity of the analysis. The calibration curve was obtained in the predefined range 25-329 ng/L with R2 larger than 0.995. Normalized matrix varied between 89.7 % and 113.5%. The method showed sufficient accuracy and precision - accuracy in the range 89.7 %-113.9 %, and precision between 2.3% and 5.4%.ConclusionsThe proposed method is validated according to current EMA/FDA industrial guidance for bioanalysis and offers an appropriate level of sensitivity and sufficient accuracy and precision.     

Surface-enhanced laser desorption ionization/time-of-flight (SELDI-TOF) mass spectrometry (MS) as a phenotypic method for rapid identification of antibiotic resistance

Based on experiments with 10 defined strains of Escherichia coli, we present a new method for bacterial phenotyping using SELDI-TOF mass spectrometry. Changes in bacterial protein profiles in the context of the time of cultivation and the antibiotic environment were minimal. Proteom subprofiling may further distinguish between strains with specific susceptibility to antimicrobials. Mass spec-based methods may become common in the future of bacterial pathogen identification in clinical microbiology diagnostics.     

A simple and efficient maleimide-based approach for peptide extension with a cysteine-containing peptide phage library

Although peptide-based molecules are known to have therapeutic potential, the generation of phage focused libraries to optimize peptides is effort-consuming. A chemical method is developed to extend a maleimide-conjugated peptide with a cysteine-containing random-peptide phage display library. As a proof of concept, a 15-mer epidermal growth factor receptor (EGFR)-binding peptide was synthesized with a maleimide group at its C-terminus and then conjugated to the cysteine-containing library. After panning and screening, several extended peptides were discovered and tested to have a higher affinity to EGFR. This strategy can have broad utility to optimize pharmacophores of any modalities (peptides, unnatural peptides, drug conjugates) capable of bearing a maleimide group     

Development and validation of a high-throughput method for the quantitative analysis of d-amphetamine in rat blood using liquid chromatography/MS on a hybrid triple quadrupole-linear ion trap mass spectrometer and its application to a pharmacokinetic study

Amphetamines are a group of sympathomimetic drugs that exhibit strong central nervous system stimulant effects. d-Amphetamine ((+)-alpha-methylphenetylamine) is the parent drug in this class to which all others are structurally related. In drug discovery, d-amphetamine is extensively used either for the exploration of novel mechanisms involving the catecholaminergic system, or for the validation of new behavioural animal models. Due to this extensive use of d-amphetamine in drug research and its interest in toxicologic–forensic investigation, a specific and high-throughput method, with minimal sample preparation, is necessary for routine analysis of d-amphetamine in biological samples. We propose here a sensitive, specific and high-throughput bioanalytical method for the quantitative determination of d-amphetamine in rat blood using MS³ scan mode on a hybrid triple quadrupole-linear ion trap mass spectrometer (LC–MS/MS/MS). Blood samples, following dilution with water, were prepared by fully automated protein precipitation with acetonitrile containing an internal standard. The chromatographic separation was achieved on a Waters XTerra C18 column (2.1 mm × 30 mm, 3.5 μm) using gradient elution at a flow rate of 1.0 mL/min over a 2 min run time. An Applied Biosystems API4000 QTRAP™ mass spectrometer equipped with turbo ion-spray ionization source was operated simultaneously in MS³ scan mode for the d-amphetamine and in multiple reaction monitoring (MRM) for the internal standard. The MS/MS/MS ion transition monitored was m/z 136.1 → 119.1 → 91.1 for the quantitation of d-amphetamine and for the internal standard (rolipram) the MS/MS ion transition monitored was m/z 276.1 → 208.2. The linear dynamic range was established over the concentration range 0.5–1000 ng/mL (r² = 0.9991). The method was rugged and sensitive with a lower limit of quantification (LLOQ) of 0.5 ng/mL. All the validation data, such as accuracy, precision, and inter-day repeatability, were within the required limits. This method was successfully applied to evaluate the pharmacokinetics of d-amphetamine in rat. On a more general extent, this work demonstrated that the selectivity of the fragmentation pathway (MS³) can be used as alternative approach to significantly improve detection capability in complex situation (e.g., small molecules in complex matrices) rather than increasing time for sample preparation and chromatographic separation.