UVnovo: A de Novo Sequencing Algorithm Using Single Series of Fragment Ions via Chromophore Tagging and 351 nm Ultraviolet Photodissociation Mass Spectrometry

Algorithms for de-novo sequencing of peptides by tandem mass spectrometry: A review

Peptide sequencing is of great significance to fundamental and applied research in the fields such as chemical, biological, medicinal and pharmaceutical sciences. With the rapid development of mass spectrometry and sequencing algorithms, de-novo peptide sequencing using tandem mass spectrometry (MS/MS) has become the main method for determining amino acid sequences of novel and unknown peptides. Advanced algorithms allow the amino acid sequence information to be accurately obtained from MS/MS spectra in short time. In this review, algorithms from exhaustive search to the state-of-art machine learning and neural network for high-throughput and automated de-novo sequencing are introduced and compared. Impacts of datasets on algorithm performance are highlighted. The current limitations and promising direction of de-novo peptide sequencing are also discussed in this review.

Protein Signatures to Trace Seafood Contamination and Processing

This review presents some applications of proteomics and selected spectroscopic methods to validate certain aspects of seafood traceability. After a general introduction to traceability and the initial applications of proteomics to authenticate traceability information, it addresses the application of proteomics to trace seafood exposure to some increasingly abundant emergent health hazards with the potential to indicate the geographic/environmental origin, such as microplastics, triclosan and human medicinal and recreational drugs. Thereafter, it shows the application of vibrational spectroscopy (Fourier-Transform Infrared Spectroscopy (FTIR) and Fourier-Transform Raman Spectroscopy (FT Raman)) and Low Field Nuclear Magnetic Resonance (LF-NMR) relaxometry to discriminate frozen fish from thawed fish and to estimate the time and temperature history of frozen fillets by monitoring protein modifications induced by processing and storage. The review concludes indicating near future trends in the application of these techniques to ensure seafood safety and traceability.

Flying blind, or just flying under the radar? The underappreciated power of de novo methods of mass spectrometric peptide identification

Mass spectrometry-based proteomics is a popular and powerful method for precise and highly multiplexed protein identification. The most common method of analyzing untargeted proteomics data is called database searching, where the database is simply a collection of protein sequences from the target organism, derived from genome sequencing. Experimental peptide tandem mass spectra are compared to simplified models of theoretical spectra calculated from the translated genomic sequences. However, in several interesting application areas, such as forensics, archaeology, venomics, and others, a genome sequence may not be available, or the correct genome sequence to use is not known. In these cases, de novo peptide identification can play an important role. De novo methods infer peptide sequence directly from the tandem mass spectrum without reference to a sequence database, usually using graph-based or machine learning algorithms. In this review, we provide a basic overview of de novo peptide identification methods and applications, briefly covering de novo algorithms and tools, and focusing in more depth on recent applications from venomics, metaproteomics, forensics, and characterization of antibody drugs.

Ultraviolet Photodissociation Mass Spectrometry for Analysis of Biological Molecules

The development of new ion-activation/dissociation methods continues to be one of the most active areas of mass spectrometry owing to the broad applications of tandem mass spectrometry in the identification and structural characterization of molecules. This Review will showcase the impact of ultraviolet photodissociation (UVPD) as a frontier strategy for generating informative fragmentation patterns of ions, especially for biological molecules whose complicated structures, subtle modifications, and large sizes often impede molecular characterization. UVPD energizes ions via absorption of high-energy photons, which allows access to new dissociation pathways relative to more conventional ion-activation methods. Applications of UVPD for the analysis of peptides, proteins, lipids, and other classes of biologically relevant molecules are emphasized in this Review.

Evaluating de novo sequencing in proteomics: already an accurate alternative to database-driven peptide identification?

While peptide identifications in mass spectrometry (MS)-based shotgun proteomics are mostly obtained using database search methods, high-resolution spectrum data from modern MS instruments nowadays offer the prospect of improving the performance of computational de novo peptide sequencing. The major benefit of de novo sequencing is that it does not require a reference database to deduce full-length or partial tag-based peptide sequences directly from experimental tandem mass spectrometry spectra. Although various algorithms have been developed for automated de novo sequencing, the prediction accuracy of proposed solutions has been rarely evaluated in independent benchmarking studies. The main objective of this work is to provide a detailed evaluation on the performance of de novo sequencing algorithms on high-resolution data. For this purpose, we processed four experimental data sets acquired from different instrument types from collision-induced dissociation and higher energy collisional dissociation (HCD) fragmentation mode using the software packages Novor, PEAKS and PepNovo. Moreover, the accuracy of these algorithms is also tested on ground truth data based on simulated spectra generated from peak intensity prediction software. We found that Novor shows the overall best performance compared with PEAKS and PepNovo with respect to the accuracy of correct full peptide, tag-based and single-residue predictions. In addition, the same tool outpaced the commercial competitor PEAKS in terms of running time speedup by factors of around 12-17. Despite around 35% prediction accuracy for complete peptide sequences on HCD data sets, taken as a whole, the evaluated algorithms perform moderately on experimental data but show a significantly better performance on simulated data (up to 84% accuracy). Further, we describe the most frequently occurring de novo sequencing errors and evaluate the influence of missing fragment ion peaks and spectral noise on the accuracy. Finally, we discuss the potential of de novo sequencing for now becoming more widely used in the field.

Precision De Novo Peptide Sequencing Using Mirror Proteases of Ac-LysargiNase and Trypsin for Large-scale Proteomics

De novo peptide sequencing for large-scale proteomics remains challenging because of the lack of full coverage of ion series in tandem mass spectra. We developed a mirror protease of trypsin, acetylated LysargiNase (Ac-LysargiNase), with superior activity and stability. The mirror spectrum pairs derived from the Ac-LysargiNase and trypsin treated samples can generate full b and y ion series, which provide mutual complementarity of each other, and allow us to develop a novel algorithm, pNovoM, for de novo sequencing. Using pNovoM to sequence peptides of purified proteins, the accuracy of the sequence was close to 100%. More importantly, from a large-scale yeast proteome sample digested with trypsin and Ac-LysargiNase individually, 48% of all tandem mass spectra formed mirror spectrum pairs, 97% of which contained full coverage of ion series, resulting in precision de novo sequencing of full-length peptides by pNovoM. This enabled pNovoM to successfully sequence 21,249 peptides from 3,753 proteins and interpreted 44-152% more spectra than pNovo+ and PEAKS at a 5% FDR at the spectrum level. Moreover, the mirror protease strategy had an obvious advantage in sequencing long peptides. We believe that the combination of mirror protease strategy and pNovoM will be an effective approach for precision de novo sequencing on both single proteins and proteome samples.

Postnovo: Postprocessing Enables Accurate and FDR-Controlled de Novo Peptide Sequencing

De novo sequencing offers an alternative to database search methods for peptide identification from mass spectra. Since it does not rely on a predetermined database of expected or potential sequences in the sample, de novo sequencing is particularly appropriate for samples lacking a well-defined or comprehensive reference database. However, the low accuracy of many de novo sequence predictions has prevented the widespread use of the variety of sequencing tools currently available. Here, we present a new open-source tool, Postnovo, that postprocesses de novo sequence predictions to find high-accuracy results. Postnovo uses a predictive model to rescore and rerank candidate sequences in a manner akin to database search postprocessing tools such as Percolator. Postnovo leverages the output from multiple de novo sequencing tools in its own analyses, producing many times the length of amino acid sequence information (including both full- and partial-length peptide sequences) at an equivalent false discovery rate (FDR) compared to any individual tool. We present a methodology to reliably screen the sequence predictions to a desired FDR given the Postnovo sequence score. We validate Postnovo with multiple data sets and demonstrate its ability to identify proteins that are missed by database search even in samples with paired reference databases.

A Potential Golden Age to Come-Current Tools, Recent Use Cases, and Future Avenues for De Novo Sequencing in Proteomics

In shotgun proteomics, peptide and protein identification is most commonly conducted using database search engines, the method of choice when reference protein sequences are available. Despite its widespread use the database-driven approach is limited, mainly because of its static search space. In contrast, de novo sequencing derives peptide sequence information in an unbiased manner, using only the fragment ion information from the tandem mass spectra. In recent years, with the improvements in MS instrumentation, various new methods have been proposed for de novo sequencing. This review article provides an overview of existing de novo sequencing algorithms and software tools ranging from peptide sequencing to sequence-to-protein mapping. Various use cases are described for which de novo sequencing was successfully applied. Finally, limitations of current methods are highlighted and new directions are discussed for a wider acceptance of de novo sequencing in the community.

PepSAVI-MS reveals anticancer and antifungal cycloviolacins in Viola odorata

Widespread resistance to antimicrobial and cancer therapeutics is evolving in every country worldwide and has a direct impact on global health, agriculture and the economy. The specificity and selectivity of bioactive peptide natural products present a possible stopgap measure to address the ongoing deficit of new therapeutic compounds. PepSAVI-MS (Statistically-guided bioActive Peptides prioritized VIa Mass Spectrometry) is an adaptable method for the analysis of natural product libraries to rapidly identify bioactive peptides. This pipeline was validated via screening of the cyclotide-rich botanical species Viola odorata and identification of the known antimicrobial and anticancer cyclotide cycloviolacin O2. Herein we present and validate novel bioactivities of the anthelmintic V. odorata cyclotide, cycloviolacin O8 (cyO8), including micromolar anticancer activity against PC-3 prostate, MDA-MB-231 breast, and OVCAR-3 ovarian cancer cell lines and antifungal activity against the agricultural pathogen Fusarium graminearum. A reduction/alkylation strategy in tandem with PepSAVI-MS analysis also revealed several previously uncharacterized putatively bioactive cyclotides. Downstream implementation of ultraviolet photodissociation (UVPD) tandem mass spectrometry is demonstrated for cyO8 as a method to address traditionally difficult-to-sequence cyclotide species. This work emphasizes the therapeutic and agricultural potential of natural product bioactive peptides and the necessity of developing robust analytical tools to deconvolute nature's complexity.

Fragmentation patterns of chromophore-tagged peptides in visible laser induced dissociation

RATIONALE

Tandem mass spectrometry (MS/MS) is the pivotal tool for protein structural characterization and quantification. Identification relies on the fragmentation step of tryptic peptides in bottom-up strategy. Specificity of fragmentation can be obtained using laser-induced dissociation (LID) in the visible range, after tagging of the targeted peptides with an adequate chromophore. Backbone fragmentation is required to obtain specific fragments and confident identification. We present herein a study of fragmentation patterns of chromophore-tagged peptides in LID, showing the potential of LID methodology to provide the maximum number of fragments for further identification and quantification.

METHODS

A total of 401 cysteine-containing tryptic peptides originating from the human proteome were derivatizated on the thiol group of cysteine with a Dabcyl maleimide chromophore, which has a high photo-absorption cross section at 473 nm. The derivatized peptides were then analyzed by LID at 473 nm on a Q Exactive instrument.

RESULTS

LID spectra present a characteristic fragment at m/z 252.112 for all precursors. This product ion arises from the internal dissociation of the Dabcyl chromophore. Several peptide-backbone fragment ions are also detected. Results show the quasi absence of fragmentation at the cysteine site. This indicates that part of the energy must be redistributed across the entire system despite excitation initially localized at the chromophore. Indeed, the fragmentation mainly occurs at 3 to 5 amino acids from the derivatized cysteine residue.

CONCLUSIONS

LID of derivatized cysteine-containing peptides displays the initial fragmentation of the chromophore. As energy is redistributed all along the peptide sequence, fragmentation of the peptide backbone is also observed. Thus, LID of chromophore-tagged peptides produces adequate fragment ions, allowing both good sequence coverage for a greater confidence of identification, and a large choice of transitions for specific quantification.

Corona Discharge Suppression in Negative Ion Mode Nanoelectrospray Ionization via Trifluoroethanol Addition

Negative ion mode nanoelectrospray ionization (nESI) is often utilized to analyze acidic compounds, from small molecules to proteins, with mass spectrometry (MS). Under high aqueous solvent conditions, corona discharge is commonly observed at emitter tips, resulting in low ion abundances and reduced nESI needle lifetimes. We have successfully reduced corona discharge in negative ion mode by trace addition of trifluoroethanol (TFE) to aqueous samples. The addition of as little as 0.2% TFE increases aqueous spray stability not only in nESI direct infusion, but also in nanoflow liquid chromatography (nLC)/MS experiments. Negative ion mode spray stability with 0.2% TFE is approximately 6× higher than for strictly aqueous samples. Upon addition of 0.2% TFE to the mobile phase of nLC/MS experiments, tryptic peptide identifications increased from 93 to 111 peptides, resulting in an average protein sequence coverage increase of 18%.

SITS Derivatization of Peptides to Enhance 266 nm Ultraviolet Photodissociation (UVPD)

N-terminal derivatization of peptides with the chromogenic reagent 4-acetamido-4-isothiocyanatostilbene-2,2-disulfonic acid (SITS) is demonstrated to enhance the efficiency of 266 nm ultraviolet photodissociation (UVPD). Attachment of the chromophore results in a mass shift of 454 Da and provides significant gains in the number and abundances of diagnostic fragment ions upon UVPD. Activation of SITS-tagged peptides with 266 nm UVPD leads to many fragment ions akin to the a/b/y ions commonly produced by CID, along with other sequence ions (c, x, and z) typically accessed through higher energy pathways. Extreme bias towards C-terminal fragment ions is observed upon activation of SITS-tagged peptides using multiple 266 nm laser pulses. Due to the high reaction efficiency of the isothiocyanate coupling to the N-terminus of peptides, we demonstrate the ability to adapt this strategy to a high-throughput LC-MS/MS workflow with 266 nm UVPD. Graphical Abstract ᅟ.

Comprehensive de Novo Peptide Sequencing from MS/MS Pairs Generated through Complementary Collision Induced Dissociation and 351 nm Ultraviolet Photodissociation

We describe a strategy for de novo peptide sequencing based on matched pairs of tandem mass spectra (MS/MS) obtained by collision induced dissociation (CID) and 351 nm ultraviolet photodissociation (UVPD). Each precursor ion is isolated twice with the mass spectrometer switching between CID and UVPD activation modes to obtain a complementary MS/MS pair. To interpret these paired spectra, we modified the UVnovo de novo sequencing software to automatically learn from and interpret fragmentation spectra, provided a representative set of training data. This machine learning procedure, using random forests, synthesizes information from one or multiple complementary spectra, such as the CID/UVPD pairs, into peptide fragmentation site predictions. In doing so, the burden of fragmentation model definition shifts from programmer to machine and opens up the model parameter space for inclusion of nonobvious features and interactions. This spectral synthesis also serves to transform distinct types of spectra into a common representation for subsequent activation-independent processing steps. Then, independent from precursor activation constraints, UVnovo's de novo sequencing procedure generates and scores sequence candidates for each precursor. We demonstrate the combined experimental and computational approach for de novo sequencing using whole cell E. coli lysate. In benchmarks on the CID/UVPD data, UVnovo assigned correct full-length sequences to 83% of the spectral pairs of doubly charged ions with high-confidence database identifications. Considering only top-ranked de novo predictions, 70% of the pairs were deciphered correctly. This de novo sequencing performance exceeds that of PEAKS and PepNovo on the CID spectra and that of UVnovo on CID or UVPD spectra alone. As presented here, the methods for paired CID/UVPD spectral acquisition and interpretation constitute a powerful workflow for high-throughput and accurate de novo peptide sequencing.

The potential impact of recent insights into proteomic changes associated with glaucoma

INTRODUCTION

Glaucoma, a major ocular neuropathy, is still far from being understood on a molecular scale. Proteomic workflows revealed glaucoma associated alterations in different eye components. By using state-of-the-art mass spectrometric (MS) based discovery approaches large proteome datasets providing important information about glaucoma related proteins and pathways could be generated. Corresponding proteomic information could be retrieved from various ocular sample species derived from glaucoma experimental models or from original human material (e.g. optic nerve head or aqueous humor). However, particular eye tissues with the potential for understanding the disease's molecular pathomechanism remains underrepresented. Areas covered: The present review provides an overview of the analysis depth achieved for the glaucomatous eye proteome. With respect to different eye regions and biofluids, proteomics related literature was found using PubMed, Scholar and UniProtKB. Thereby, the review explores the potential of clinical proteomics for glaucoma research. Expert commentary: Proteomics will provide important contributions to understanding the molecular processes associated with glaucoma. Sensitive discovery and targeted MS approaches will assist understanding of the molecular interplay of different eye components and biofluids in glaucoma. Proteomic results will drive the comprehension of glaucoma, allowing a more stringent disease hypothesis within the coming years.

De Novo Sequencing of Top-Down Tandem Mass Spectra: A Next Step towards Retrieving a Complete Protein Sequence

De novo sequencing of tandem (MS/MS) mass spectra represents the only way to determine the sequence of proteins from organisms with unknown genomes, or the ones not directly inscribed in a genome-such as antibodies, or novel splice variants. Top-down mass spectrometry provides new opportunities for analyzing such proteins; however, retrieving a complete protein sequence from top-down MS/MS spectra still remains a distant goal. In this paper, we review the state-of-the-art on this subject, and enhance our previously developed Twister algorithm for de novo sequencing of peptides from top-down MS/MS spectra to derive longer sequence fragments of a target protein.

Improving Performance Metrics of Ultraviolet Photodissociation Mass Spectrometry by Selective Precursor Ejection

Confident protein identifications derived from high-throughput bottom-up and top-down proteomics workflows depend on acquisition of thousands of tandem mass spectrometry (MS/MS) spectra with adequate signal-to-noise and accurate mass assignments of the fragment ions. Ultraviolet photodissociation (UVPD) using 193 nm photons has proven to be well-suited for activation and fragmentation of peptides and proteins in ion trap mass spectrometers, but the spectral signal-to-noise ratio (S/N) is typically lower than that obtained from collisional activation methods. The lower S/N is attributed to the dispersion of ion current among numerous fragment ion channels (a,b,c,x,y,z ions). In addition, frequently UVPD is performed such that a relatively large population of precursor ions remains undissociated after the UV photoactivation period in order to prevent overdissociation into small uninformative or internal fragment ions. Here we report a method to improve spectral S/N and increase the accuracy of mass assignments of UVPD mass spectra via resonance ejection of undissociated precursor ions after photoactivation. This strategy, termed precursor ejection UVPD or PE-UVPD, allows the ion trap to be filled with more ions prior to UVPD while at the same time alleviating the space charge problems that would otherwise contribute to the skewing of mass assignments and reduction of S/N. Here we report the performance gains by implementation of PE-UVPD for peptide analysis in an ion trap mass spectrometer.

Integrating Weak Anion Exchange and Ultraviolet Photodissociation Mass Spectrometry with Strategic Modulation of Peptide Basicity for the Enrichment of Sulfopeptides

Tyrosine sulfation is an important post-translational modification but remains difficult to detect in biological samples owing to its low stoichiometric abundance and the lack of effective enrichment methods. In the present study, weak anion exchange (WAX) is evaluated for the enrichment of sulfopeptides that have been modified via carbamylation to convert all primary amines to less basic carbamates. The decrease in basicity enhanced the binding of carbamylated sulfopeptides to WAX resin relative to nonsulfated peptides. Upon elution and electrospray ionization in the negative mode, ultraviolet photodissociation (UVPD) was applied for peptide sequencing. Application of the method to a tryptic digest of bovine coagulation factor V resulted in identification of sulfation on tyrosine 1513.

Top-down analysis of protein samples by de novo sequencing techniques

MOTIVATION

Recent technological advances have made high-resolution mass spectrometers affordable to many laboratories, thus boosting rapid development of top-down mass spectrometry, and implying a need in efficient methods for analyzing this kind of data.

RESULTS

We describe a method for analysis of protein samples from top-down tandem mass spectrometry data, which capitalizes on de novo sequencing of fragments of the proteins present in the sample. Our algorithm takes as input a set of de novo amino acid strings derived from the given mass spectra using the recently proposed Twister approach, and combines them into aggregated strings endowed with offsets. The former typically constitute accurate sequence fragments of sufficiently well-represented proteins from the sample being analyzed, while the latter indicate their location in the protein sequence, and also bear information on post-translational modifications and fragmentation patterns.

AVAILABILITY AND IMPLEMENTATION

Freely available on the web at http://bioinf.spbau.ru/en/twister

CONTACT

vyatkina@spbau.ru or ppevzner@ucsd.edu

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Cysteine-Selective Peptide Identification: Selenium-Based Chromophore for Selective S-Se Bond Cleavage with 266 nm Ultraviolet Photodissociation

The tremendous number of peptides identified in current bottom-up mass spectrometric workflows, although impressive for high-throughput proteomics, results in little selectivity for more targeted applications. We describe a strategy for cysteine-selective proteomics based on a tagging method that installs a S-Se bond in peptides that is cleavable upon 266 nm ultraviolet photodissociation (UVPD). The alkylating reagent, N-(phenylseleno)phthalimide (NPSP), reacts with free thiols in cysteine residues and attaches a chromogenic benzeneselenol (SePh) group. Upon irradiation of tagged peptides with 266 nm photons, the S-Se bond is selectively cleaved, releasing a benzeneselenol moiety corresponding to a neutral loss of 156 Da per cysteine. Herein we demonstrate a new MS/MS scan mode, UVPDnLossCID, which facilitates selective screening of cysteine-containing peptides. A "prescreening" event occurs by activation of the top N peptide ions by 266 nm UVPD. Peptides exhibiting a neutral loss corresponding to one or more SePh groups are reactivated and sequenced by CID. Because of the low frequency of cysteine in the proteome, unique cysteine-containing peptides may serve as surrogates for entire proteins. UVPDnLossCID does not generate as many peptide spectrum matches (PSMs) as conventional bottom-up methods; however, UVPDnLossCID provides far greater selectivity.