Interpretation Of Tandem Mass Spectra Research Articles

Abstract 7414: Claire: a search engine leveraging deep databases for reliable detection of peptides, with a special focus on proteogenomic applications

Abstract As the field of cancer diagnostics and treatment evolves, the significance of peptides characterized by post-translational modifications and amino acid substitutions is becoming increasingly prominent. These molecular alterations frequently offer critical insights into tumor biology, aiding the development of targeted therapies and methods for personalized medicine. However, despite ongoing advances in shotgun proteomics, the field still faces multiple challenges for the reliable detection of rare peptide forms, for instance, amino acid substitutions when the corresponding DNA or RNA sequencing is unavailable. As a response to these challenges, our group has developed Claire—a probabilistic search engine employing large peptide databases for detection. These databases, often on the terabyte scale, further incorporate the estimates of peptides' prior probabilities to improve detection accuracy and utilize several optimizations to allow fast interpretation of tandem mass spectra. Claire outperformed state-of-the-art software, such as MSFragger and TagGraph when evaluated on the protein-level detection of single nucleotide variants in the public NCI60 proteome dataset. Further, Claire's analysis of a range of NCI60 datasets revealed high protein-level mutational burdens in genomically unstable cancer cell lines and detected mislabeling and contamination across several omics datasets. In a clinical domain, Claire discerned the hypermutation status of colorectal cancer patients' tumors, identifying candidates suitable for immunotherapy. Protein-level variation in peripheral blood mononuclear cells also recognized individuals, monozygotic twins aside, revealing the pseudonymous nature of germline proteome datasets, and raising the need for their protection. From a computational perspective, Claire can be run as a standalone software in the Linux operating system, or its capabilities accessed remotely using an interface on our cloud computing infrastructure. Claire has thus shown remarkable potential in enhancing peptide detection, offers substantial advancements for both clinical and research applications, and allows direct incorporation of its capabilities into various computational workflows. Citation Format: Miroslav Hruska, Petr Dzubak, Marian Hajduch. Claire: a search engine leveraging deep databases for reliable detection of peptides, with a special focus on proteogenomic applications [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 7414.

Mechanistic Study into Free Radical-Activated Glycan Dissociations through Isotope-Labeled Cellobioses.

Inspired by the electron-activated dissociation technique, the most potent tool for glycan characterization, we recently developed free radical reagents for glycan structural elucidation. However, the underlying mechanisms of free radical-induced glycan dissociation remain unclear and, therefore, hinder the rational optimization of the free radical reagents and the interpretation of tandem mass spectra, especially the accurate assignment of the relatively low-abundant but information-rich ions. In this work, we selectively incorporate the 13C and/or 18O isotopes into cellobiose to study the mechanisms for free radical-induced dissociation of glycans. The eight isotope-labeled cellobioses include 1-13C, 3-13C, 1'-13C, 2'-13C, 3'-13C, 4'-13C, 5'-13C, and 1'-13C-4-18O-cellobioses. Upon one-step collisional activation, cross-ring (X ions), glycosidic bond (Y-, Z-, and B-related ions), and combinational (Y1 + 0,4X0 ion) cleavages are generated. These fragment ions can be unambiguously assigned and confirmed by the mass difference of isotope labeling. Importantly, the relatively low-abundant but information-rich ions, such as 1,5X0 + H, 1,4X0 + H, 2,4X0 + H-OH, Y1 + 0,4X0, 2,5X1-H, 3,5X0-H, 0,3X0-H, 1,4X0-H, and B2-3H, are confidently assigned. The mechanisms for the formations of these ions are investigated and supported by quantum chemical calculations. These ions are generally initiated by hydrogen abstraction followed by sequential β-elimination and/or radical migration. Here, the mechanistic study for free radical-induced glycan dissociation allows us to interpret all of the free radical-induced fragment ions accurately and, therefore, enables the differentiation of stereochemical isomers. Moreover, it provides fundamental knowledge for the subsequent development of bioinformatics tools to interpret the complex free radical-induced glycan spectra.

Combining Chemical Knowledge and Quantum Calculation for Interpreting Low-Energy Product Ion Spectra of Metabolite Adduct Ions: Sodiated Diterpene Diester Species as a Case Study.

We investigated the product ion spectra of [M + Na]+ from diterpene diester species and low molecular mass metabolites analyzed by electrospray ionization (ESI). Mainly, the formation of protonated salt structures was proposed to explain the observed neutral losses of carboxylic acids. It also facilitates understanding sodium retention on product ions or on neutral losses. In addition, the occurrence of consecutive carboxylic acid losses is rather unexpected under resonant excitation conditions. Quantum calculation demonstrated that the exothermic character of such neutral losses can represent a relevant explanation. There is no doubt that the formation and role of the protonated salt structures will be helpful for a better understanding and software-assisted interpretation of tandem mass spectra from small molecules, especially in the ever-growing metabolomics field.

Comprehensive Identification of Glycosphingolipids in Human Plasma Using Hydrophilic Interaction Liquid Chromatography-Electrospray Ionization Mass Spectrometry.

Glycosphingolipids (GSL) represent a highly heterogeneous class of lipids with many cellular functions, implicated in a wide spectrum of human diseases. Their isolation, detection, and comprehensive structural analysis is a challenging task due to the structural diversity of GSL molecules. In this work, GSL subclasses are isolated from human plasma using an optimized monophasic ethanol–water solvent system capable to recover a broad range of GSL species. Obtained deproteinized plasma is subsequently purified and concentrated by C18-based solid-phase extraction (SPE). The hydrophilic interaction liquid chromatography coupled to electrospray ionization linear ion trap tandem mass spectrometry (HILIC-ESI-LIT-MS/MS) is used for GSL analysis in the human plasma extract. Our results provide an in-depth profiling and structural characterization of glycosphingolipid and some phospholipid subclasses identified in the human plasma based on their retention times and the interpretation of tandem mass spectra. The structural composition of particular lipid species is readily characterized based on the detailed interpretation of mass spectrometry (MS) and tandem mass spectrometry (MS/MS) spectra and further confirmed by specific fragmentation behavior following predictable patterns, which yields to the unambiguous identification of 154 GSL species within 7 lipid subclasses and 77 phospholipids representing the highest number of GSL species ever reported in the human plasma. The developed HILIC-ESI-MS/MS method can be used for further clinical and biological research of GSL in the human blood or other biological samples.

The Journey Is the Reward, a Taoist Proverb: John B. Fenn Award for Distinguished Contribution in Mass Spectrometry Lecture.

This account provided by John Yates describes his incredible path as a scientist, emphasizing key decisions along the way that shaped his career and led to his landmark contributions to the field of mass spectrometry. Although perhaps best known is the development of the SEQUEST algorithm for automated interpretation of tandem mass spectra of peptides, John's achievements have spanned the field of proteomics and had major impact on the ability to address and solve significant biological problems.

Top-down analysis of novel synthetic branched proteins.

A strategy for top-down analysis of branched proteins has been reported earlier, which relies on electron transfer dissociation assisted by collisional activation, and software designed for graphic interpretation of tandem mass spectra and adapted for branched proteins. In the present study, the strategy is applied to identify unknown and novel products of reactions in which rationally mutated proteoforms of Rub1 are used to probe the selectivity of E1 and E2 enzymes normally active in ubiquitination. To test and demonstrate this application, components and attachment sites of three branched dimers are deduced and the mutations are confirmed.

Software for Peak Finding and Elemental Composition Assignment for Glycosaminoglycan Tandem Mass Spectra

Glycosaminoglycans (GAGs) covalently linked to proteoglycans (PGs) are characterized by repeating disaccharide units and variable sulfation patterns along the chain. GAG length and sulfation patterns impact disease etiology, cellular signaling, and structural support for cells. We and others have demonstrated the usefulness of tandem mass spectrometry (MS2) for assigning the structures of GAG saccharides; however, manual interpretation of tandem mass spectra is time-consuming, so computational methods must be employed. In the proteomics domain, the identification of monoisotopic peaks and charge states relies on algorithms that use averagine, or the average building block of the compound class being analyzed. Although these methods perform well for protein and peptide spectra, they perform poorly on GAG tandem mass spectra, because a single average building block does not characterize the variable sulfation of GAG disaccharide units. In addition, it is necessary to assign product ion isotope patterns to interpret the tandem mass spectra of GAG saccharides. To address these problems, we developed GAGfinder, the first tandem mass spectrum peak finding algorithm developed specifically for GAGs. We define peak finding as assigning experimental isotopic peaks directly to a given product ion composition, as opposed to deconvolution or peak picking, which are terms more accurately describing the existing methods previously mentioned. GAGfinder is a targeted, brute force approach to spectrum analysis that uses precursor composition information to generate all theoretical fragments. GAGfinder also performs peak isotope composition annotation, which is typically a subsequent step for averagine-based methods. Data are available via ProteomeXchange with identifier PXD009101.

Large-scale identification and visualization of N-glycans with primary structures using GlySeeker.

Most of the current popular tandem mass spectrometers have the capability of resolving the primary structures (monosaccharide composition, sequence and linkage) of N-glycans; however, compositions or putative structures have mostly been reported so far. Identification and visualization tools of N-glycans are needed. The isotopic mass-to-charge ratio and envelope fingerprinting algorithm, which has been successfully used for intact protein database search and identification, was adapted for N-glycan database search, and a stand-alone N-glycan database search engine, GlySeeker, for automated N-glycan identification and visualization was developed and successfully benchmarked. Both pseudo 2D graph and one-line text formats with one-letter symbols for monosaccharides were proposed for representing N-glycans. N-glycans were identified with comprehensive interpretation of product ions and false discovery rate (FDR) control. In a database search of reversed-phase liquid chromatography/tandem mass spectrometry (RPLC/MS/MS) datasets of the N-glycome enriched from OVCAR-3 ovarian cancer cells, with FDR ≤1% and number of best hits (NoBHs) = 1-30, 1525N-glycans with comprehensive primary structural information (composition, sequence and linkage) were identified and visualized; among these 1525N-glycans, 559 had NoBHs = 1, i.e. their structures were uniquely identified. This represents a large-scale identification and visualization of N-glycans with primary structures from tandem mass spectra. A stand-alone N-glycan database search engine called GlySeeker has been developed for large-scale identification and visualization of N-glycans with comprehensive interpretation of tandem mass spectra and FDR control.

S- to N-Palmitoyl Transfer During Proteomic Sample Preparation.

N-palmitoylation has been reported in a number of proteins and suggested to play an important role in protein localization and functions. However, it remains unclear whether N-palmitoylation is a direct enzyme-catalyzed process, or results from intramolecular S- to N-palmitoyl transfer. Here, using the S-palmitoyl peptide standard, GCpalmLGNAK, as the model system, we observed palmitoyl migration from the cysteine residue to either the peptide N-terminus or the lysine side chain during incubation in both neutral and slightly basic buffers commonly used in proteomic sample preparation. Palmitoyl transfer can take place either intra- or inter-molecularly, with the peptide N-terminus being the preferred migration site, presumably because of its lower basicity. The extent of intramolecular palmitoyl migration was low in the system studied, as it required the formation of an entropically unfavored macrocycle intermediate. Intermolecular palmitoyl transfer, however, remained a tangible problem, and may lead to erroneous reporting of in vivo N-palmitoylation. It was found that addition of the MS-compatible detergent RapiGest could significantly inhibit intermolecular palmitoyl transfer, as well as thioester hydrolysis and DTT-induced thioester cleavage. Finally, palmitoyl transfer from the cysteine residue to the peptide N-terminus can also occur in the gas phase, during collision-induced dissociation, and result in false identification of N-palmitoylation. Therefore, one must be careful with both sample preparation and interpretation of tandem mass spectra in the study of N-palmitoylation. Graphical Abstract ᅟ.

The H-Index of ‘An Approach to Correlate Tandem Mass Spectral Data of Peptides with Amino Acid Sequences in a Protein Database’

Over 20years ago a remarkable paper was published in the Journal of American Society for Mass Spectrometry. This paper from Jimmy Eng, Ashley McCormack, and John Yates described the use of protein databases to drive the interpretation of tandem mass spectra of peptides. This paper now has over 3660 citations and continues to average more than 260 per year over the last decade. This is an amazing scientific achievement. The reason for this is the paper was a cutting edge development at the moment in time when genomes of organisms were being sequenced, protein and peptide mass spectrometry was growing into the field of proteomics, and the power of computing was growing quickly in accordance with Moore's law. This work by the Yates lab grew in importance as genomics, proteomics, and computation all advanced and eventually resulted in the widely used SEQUEST algorithm and platform for the analysis of tandem mass spectrometry data. This commentary provides an analysis of the impact of this paper by analyzing the citations it has generated and the impact of these citing papers. Graphical Abstract ᅟ.

CFM-ID: a web server for annotation, spectrum prediction and metabolite identification from tandem mass spectra.

CFM-ID is a web server supporting three tasks associated with the interpretation of tandem mass spectra (MS/MS) for the purpose of automated metabolite identification: annotation of the peaks in a spectrum for a known chemical structure; prediction of spectra for a given chemical structure and putative metabolite identification—a predicted ranking of possible candidate structures for a target spectrum. The algorithms used for these tasks are based on Competitive Fragmentation Modeling (CFM), a recently introduced probabilistic generative model for the MS/MS fragmentation process that uses machine learning techniques to learn its parameters from data. These algorithms have been extensively tested on multiple datasets and have been shown to out-perform existing methods such as MetFrag and FingerId. This web server provides a simple interface for using these algorithms and a graphical display of the resulting annotations, spectra and structures. CFM-ID is made freely available at http://cfmid.wishartlab.com.

MS/MS Spectra Interpretation as a Statistical–Mechanics Problem

We describe a new method for peptide sequencing based on the mapping of the interpretation of tandem mass spectra onto the analysis of the equilibrium distribution of a suitably defined physical model, whose variables describe the positions of the fragmentation sites along a discrete mass index. The model is governed by a potential energy function that, at present, we derive ad hoc from the distribution of peaks in a data set of experimental spectra. The statistical-physics perspective prompts for a consistent and unified approach to de novo and database-search methods, which is a distinctive feature of this approach over alternative ones: the characterization of the ground state of the model allows the de novo identification of the precursor peptide; the study of the thermodynamic variables as a function of the (fictitious) temperature gives insight on the quality of the prediction, while the probability profiles at nonzero temperature reveal, on one hand, which fragments are more reliably predicted. On the other hand, they can be used as a spectrum-adapted, a posteriori score for database search. Results obtained with two different test data sets reveal a performance similar to that of other de novo and database-search methods, which is reasonable, given the lack of an aggressive optimization of the energy function at this stage. An important feature of the method is that it is quite general and can be applied with different choices of the energy function: we discuss its possible improvements and generalizations.

Proteomic analysis of formalin-fixed paraffin-embedded colorectal cancer tissue using tandem mass tag protein labeling

In clinical research, repositories of biological samples form a rich source of clinical material for biomarker studies. Banked material, however, is often not stored in optimal conditions regarding the technology used for biomarker research. A case in point is formalin-fixed paraffin-embedded (FFPE) tissue that could be used to obtain large cohorts of samples over a short period of time, as these tissues are routinely prepared for pathological analysis. However, in the context of mass spectrometry based peptide-centric proteomics, protein extraction and identification can be hampered by formalin-induced crosslinking. Furthermore, the molecular formalin crosslinks might be entangled differently across various samples, making it more difficult to reproducibly extract the same proteins from different samples. In this study, we establish the crosslink variability using Tandem Mass Tag (TMT) protein labeling followed by digestion, separation, identification and quantification of proteins extracted from FFPE colorectal cancer and paired healthy tissues. Moreover, by applying de novo interpretation of tandem mass spectra and subsequent analysis by Peaks PTM, unspecified modifications could be elucidated, leading to increased protein and proteome coverage. This approach might be useful for future FFPE proteomics studies.

Analysis of different synthetic homopolymers by the use of a new calculation software for tandem mass spectra

The manual interpretation of tandem mass spectra of synthetic polymers is very time-consuming. Therefore, a new software tool was developed to accelerate the interpretation of spectra obtained without requiring any further knowledge about the polymer class or the fragmentation behavior under high-energy collision-induced dissociation (CID) conditions. The software only requires an alphabetical list of elements and a peak list of the measured substance as an xml file for the evaluation of the chosen mass spectrum. Tandem mass spectra of different homopolymers, like poly(2-oxazoline)s, poly(ethylene glycol) and poly(styrene), were interpreted by the new software tool. This contribution describes a fast and automated software tool for the rapid analysis of homopolymers.

Physicochemical/Thermodynamic Framework for the Interpretation of Peptide Tandem Mass Spectra

The interpretation of tandem mass spectra of peptides from collision-induced dissociation is discussed from the perspective of a multinomial data analysis problem and from the perspective of statis...

Interpretation of tandem mass spectra obtained from cyclic nonribosomal peptides.

Natural and non-natural cyclic peptides are a crucial component in drug discovery programs because of their considerable pharmaceutical properties. Cyclosporin, microcystins, and nodularins are all notable pharmacologically important cyclic peptides. Because these biologically active peptides are often biosynthesized nonribosomally, they often contain nonstandard amino acids, thus increasing the complexity of the resulting tandem mass spectrometry data. In addition, because of the cyclic nature, the fragmentation patterns of many of these peptides showed much higher complexity when compared to related counterparts. Therefore, at the present time it is still difficult to annotate cyclic peptides MS/MS spectra. In this current work, an annotation program was developed for the annotation and characterization of tandem mass spectra obtained from cyclic peptides. This program, which we call MS-CPA is available as a web tool (http://lol.ucsd.edu/ms-cpa_v1/Input.py). Using this program, we have successfully annotated the sequence of representative cyclic peptides, such as seglitide, tyrothricin, desmethoxymajusculamide C, dudawalamide A, and cyclomarins, in a rapid manner and also were able to provide the first-pass structure evidence of a newly discovered natural product based on predicted sequence. This compound is not available in sufficient quantities for structural elucidation by other means such as NMR. In addition to the development of this cyclic annotation program, it was observed that some cyclic peptides fragmented in unexpected ways resulting in the scrambling of sequences. In summary, MS-CPA not only provides a platform for rapid confirmation and annotation of tandem mass spectrometry data obtained with cyclic peptides but also enables quantitative analysis of the ion intensities. This program facilitates cyclic peptide analysis, sequencing, and also acts as a useful tool to investigate the uncommon fragmentation phenomena of cyclic peptides and aids the characterization of newly discovered cyclic peptides encountered in drug discovery programs.

MODi : a powerful and convenient web server for identifying multiple post-translational peptide modifications from tandem mass spectra

MODi () is a powerful and convenient web service that facilitates the interpretation of tandem mass spectra for identifying post-translational modifications (PTMs) in a peptide. It is powerful in that it can interpret a tandem mass spectrum even when hundreds of modification types are considered and the number of potential PTMs in a peptide is large, in contrast to most of the methods currently available for spectra interpretation that limit the number of PTM sites and types being used for PTM analysis. For example, using MODi, one can consider for analysis both the entire PTM list published on the unimod webpage () and user-defined PTMs simultaneously, and one can also identify multiple PTM sites in a spectrum. MODi is convenient in that it can take various input file formats such as .mzXML, .dta, .pkl and .mgf files, and it is equipped with a graphical tool called MassPective developed to display MODi's output in a user-friendly manner and helps users understand MODi's output quickly. In addition, one can perform manual de novo sequencing using MassPective.

The Power and the Limitations of Cross-Species Protein Identification by Mass Spectrometry-driven Sequence Similarity Searches

Mass spectrometry-driven BLAST (MS BLAST) is a database search protocol for identifying unknown proteins by sequence similarity to homologous proteins available in a database. MS BLAST utilizes redundant, degenerate, and partially inaccurate peptide sequence data obtained by de novo interpretation of tandem mass spectra and has become a powerful tool in functional proteomic research. Using computational modeling, we evaluated the potential of MS BLAST for proteome-wide identification of unknown proteins. We determined how the success rate of protein identification depends on the full-length sequence identity between the queried protein and its closest homologue in a database. We also estimated phylogenetic distances between organisms under study and related reference organisms with completely sequenced genomes that allow substantial coverage of unknown proteomes.

MultiTag: multiple error-tolerant sequence tag search for the sequence-similarity identification of proteins by mass spectrometry.

The characterization of proteomes by mass spectrometry is largely limited to organisms with sequenced genomes. To identify proteins from organisms with unsequenced genomes, database sequences from related species must be employed for sequence-similarity protein identifications. Peptide sequence tags (Mann, 1994) have been used successfully for the identification of proteins in sequence databases using partially interpreted tandem mass spectra of tryptic peptides. We have extended the ability of sequence tag searching to the identification of proteins whose sequences are yet unknown but are homologous to known database entries. The MultiTag method presented here assigns statistical significance to matches of multiple error-tolerant sequence tags to a database entry and ranks alignments by their significance. The MultiTag approach has the distinct advantage over other sequence-similarity approaches of being able to perform sequence-similarity identifications using only very short (2-4) amino acid residue stretches of peptide sequences, rather than complete peptide sequences deduced by de novo interpretation of tandem mass spectra. This feature facilitates the identification of low abundance proteins, since noisy and low-intensity tandem mass spectra can be utilized.

Quantitation and facilitated de novo sequencing of proteins by isotopic N-terminal labeling of peptides with a fragmentation-directing moiety.

We describe a method for comparative quantitation and de novo peptide sequencing of proteins separated either by standard chromatographic methods or by one- and two-dimensional polyacrylamide gel electrophoresis. The approach is based on the use of an isotopically labeled reagent to quantitate (by mass spectrometry) the ratio of peptides from digests of a protein being expressed under different conditions. The method allows quantitation of the changes occurring in spots or bands that contain more than one protein and has a greater dynamic range than most staining methods. Since the reagent carries a fixed positive charge under acidic conditions and labels only the N-terminal of peptides, the interpretation of tandem mass spectra to obtain sequence information is greatly simplified. The sequences can easily be extracted for homology searches instead of using indirect mass spectral-based searches and are independent of posttranslational modifications.