Peaks In Mass Spectra Research Articles

Sequence-to-sequence translation from mass spectra to peptides with a transformer model

A fundamental challenge in mass spectrometry-based proteomics is the identification of the peptide that generated each acquired tandem mass spectrum. Approaches that leverage known peptide sequence databases cannot detect unexpected peptides and can be impractical or impossible to apply in some settings. Thus, the ability to assign peptide sequences to tandem mass spectra without prior information—de novo peptide sequencing—is valuable for tasks including antibody sequencing, immunopeptidomics, and metaproteomics. Although many methods have been developed to address this problem, it remains an outstanding challenge in part due to the difficulty of modeling the irregular data structure of tandem mass spectra. Here, we describe Casanovo, a machine learning model that uses a transformer neural network architecture to translate the sequence of peaks in a tandem mass spectrum into the sequence of amino acids that comprise the generating peptide. We train a Casanovo model from 30 million labeled spectra and demonstrate that the model outperforms several state-of-the-art methods on a cross-species benchmark dataset. We also develop a version of Casanovo that is fine-tuned for non-enzymatic peptides. Finally, we demonstrate that Casanovo’s superior performance improves the analysis of immunopeptidomics and metaproteomics experiments and allows us to delve deeper into the dark proteome.

Tentative estimates of B(X(3872)→π0π0χc1) and B(X(3872)→π+π−χc1)

The rates of the X(3872)→π0π0χc1 and X(3872)→π+π−χc1 decays are estimated in the model of the triangle loop diagrams with charmed D*D¯D and D¯*DD¯ mesons in the loops. There are the triangle logarithmic singularities in the physical region of the X(3872)→π0π0χc1 decay which manifest themselves as narrow peaks in the π0χc1 mass spectrum near the D0D¯0 threshold. The model predicts approximately the same branching fractions of the X(3872)→π0π0χc1 and X(3872)→π+π−χc1 decays at the level of about (0.8–1.7)×10−4. A distinct prediction of the model is the value of the ratio R=B(X(3872)→π+π−χc1)/B(X(3872)→π0π0χc1)≈1.1. It weakly depends on the X(3872) resonance parameters and indicates a significant violation of the isotopic symmetry according to which one would expect R=2. Published by the American Physical Society 2024

Characteristic structures of liquid crystal monomers in EI-MS analysis and the potential application in suspect screening

Liquid crystal monomers (LCMs) are of emerging concern due to their ubiquitous presence in indoor and outdoor environments and their potential negative impacts on human health and ecosystems. Suspect screening approaches have been developed to monitor thousands of LCMs that could enter the environment, but an updated suspect list of LCMs is difficult to maintain given the rapid development of material innovations. To facilitate suspect screening for LCMs, in-silico mass fragmentation model and quantitative structure-activity relationship (QSPR) models were applied to predict electron ionization (EI) mass spectra of LCMs. The in-silico model showed limited predictive power for EI mass spectra, while the QSPR models trained with 437 published mass spectra of LCMs achieved an acceptable absolute error of 12 percentage points in predicting the relative intensity of the molecular ion, but failed to predict the mass-to-charge ratio of the base peak. A total of 41 characteristic structures were identified from an updated suspect list of 1606 LCMs. Multi-phenyl groups form the rigid cores of 85% of LCMs and produce 154 characteristic peaks in EI mass spectra. Monitoring the characteristic structures and fragments of LCMs may help identify new LCMs with the same rigid cores as those in the suspect list.

Computation of the masses of the elementary particles

An approach to gauge theory in the context of locally conformally flat space–time is described. It is discussed how there are a number of natural principal bundles associated with any given locally conformally flat space–time X. The simplest of these principal bundles is the bundle PX(G) with structure group G = U(2, 2). An 11-dimensional bundle Q with structure group a certain seven-dimensional group K is constructed by a method involving a reduction of structure group for the bundle PX(G). It is shown how the gauge groups U(1), SU(2), and SU(3) can be derived from the geometry of locally conformally flat space–time. Fock spaces of multiparticle states for the fields of the standard model are constructed in the context of bundles with these groups as structure groups. Scattering and other particle interaction processes are defined in terms of linear maps between multiparticle state spaces. A technique for computing analytically and/or computationally the masses of the elementary particles is described. This method involves the computation of a certain quantity called the integral mass spectrum for a given family of particles and then the masses of the particles in the family are determined to be the locations of the peaks of the integral mass spectrum. The method is applied successfully in the electroweak sector to the cases of the charged leptons, μ and τ, and the Z0 particle.

Search for direct production of GeV-scale resonances decaying to a pair of muons in proton-proton collisions at s\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$ \\sqrt{s} $$\\end{document} = 13 TeV

A search for direct production of low-mass dimuon resonances is performed using s\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$ \\sqrt{s} $$\\end{document} = 13 TeV proton-proton collision data collected by the CMS experiment during the 2017–2018 operation of the CERN LHC with an integrated luminosity of 96.6 fb−1. The search exploits a dedicated high-rate trigger stream that records events with two muons with transverse momenta as low as 3 GeV but does not include the full event information. The search is performed by looking for narrow peaks in the dimuon mass spectrum in the ranges of 1.1–2.6 GeV and 4.2–7.9 GeV. No significant excess of events above the expectation from the standard model background is observed. Model-independent limits on production rates of dimuon resonances within the experimental fiducial acceptance are set. Competitive or world’s best limits are set at 90% confidence level for a minimal dark photon model and for a scenario with two Higgs doublets and an extra complex scalar singlet (2HDM+S). Values of the squared kinetic mixing coefficient ε2 in the dark photon model above 10−6 are excluded over most of the mass range of the search. In the 2HDM+S, values of the mixing angle sin(θH) above 0.08 are excluded over most of the mass range of the search with a fixed ratio of the Higgs doublets vacuum expectation tan β = 0.5.

Multi-Parameter Auto-Tuning Algorithm for Mass Spectrometer Based on Improved Particle Swarm Optimization.

Quadrupole mass spectrometers (QMS) are widely used for clinical diagnosis and chemical analysis. To obtain the best experimental results, mass spectrometers must be calibrated to an ideal setting before use. However, tuning the current QMS is challenging. Traditional tuning techniques possess low automation levels and rely primarily on skilled engineers. Therefore, in this study, we propose an innovative auto-tuning algorithm for QMS based on the improved particle swarm optimization (PSO) algorithm to automatically find the optimal solution of QMS parameters and make the QMS reach the optimal state. The improved PSO algorithm is combined with simulated annealing, multiple inertia weights, dynamic boundaries, and other methods to prevent the traditional PSO algorithm from the issue of a local optimal solution and premature convergence. According to the characteristics of the mass spectrum peaks, a termination function is proposed to simplify the termination conditions of the PSO algorithm and further improve the automation level of the mass spectrometer. The results of auto-calibration testing of resolution and mass axis show that both resolution and mass axis calibration could effectively meet the requirements of mass spectrometry experiments. By the experiment of auto-optimization testing of lens and ion source parameters, these parameters were all in the vicinity of the optimal solution, which achieved the expected performance. Through numerous experiments, the reproducibility of the algorithm was established as meeting the auto-tuning function of the QMS. The proposed method can automatically tune the mass spectrometer from its non-optimal condition to the optimal one, which can effectively reduce the tuning difficulty of QMS.

RNxQuest: An Extension to the xQuest Pipeline Enabling Analysis of Protein-RNA Cross-Linking/Mass Spectrometry Data.

Cross-linking and mass spectrometry (XL-MS) workflows are increasingly popular techniques for generating low-resolution structural information about interacting biomolecules. xQuest is an established software package for analysis of protein-protein XL-MS data, supporting stable isotope-labeled cross-linking reagents. Resultant paired peaks in mass spectra aid sensitivity and specificity of data analysis. The recently developed cross-linking of isotope-labeled RNA and mass spectrometry (CLIR-MS) approach extends the XL-MS concept to protein-RNA interactions, also employing isotope-labeled cross-link (XL) species to facilitate data analysis. Data from CLIR-MS experiments are broadly compatible with core xQuest functionality, but the required analysis approach for this novel data type presents several technical challenges not optimally served by the original xQuest package. Here we introduce RNxQuest, a Python package extension for xQuest, which automates the analysis approach required for CLIR-MS data, providing bespoke, state-of-the-art processing and visualization functionality for this novel data type. Using functions included with RNxQuest, we evaluate three false discovery rate control approaches for CLIR-MS data. We demonstrate the versatility of the RNxQuest-enabled data analysis pipeline by also reanalyzing published protein-RNA XL-MS data sets that lack isotope-labeled RNA. This study demonstrates that RNxQuest provides a sensitive and specific data analysis pipeline for detection of isotope-labeled XLs in protein-RNA XL-MS experiments.

Searches for new phenomena in events with two leptons, jets, and missing transverse momentum in 139 fb^{-1} of varvec{sqrt{s}}=13 TeV varvec{pp} collisions with the ATLAS detector

Searches for new phenomena inspired by supersymmetry in final states containing an e^+e^- or mu ^+mu ^- pair, jets, and missing transverse momentum are presented. These searches make use of proton–proton collision data with an integrated luminosity of 139~text {fb}^{-1}, collected during 2015–2018 at a centre-of-mass energy sqrt{s}=13~TeV by the ATLAS detector at the Large Hadron Collider. Two searches target the pair production of charginos and neutralinos. One uses the recursive-jigsaw reconstruction technique to follow up on excesses observed in 36.1~text {fb}^{-1} of data, and the other uses conventional event variables. The third search targets pair production of coloured supersymmetric particles (squarks or gluinos) decaying through the next-to-lightest neutralino (tilde{chi }_2^0) via a slepton (tilde{ell }) or Z boson into ell ^+ell ^-tilde{chi }_1^0, resulting in a kinematic endpoint or peak in the dilepton invariant mass spectrum. The data are found to be consistent with the Standard Model expectations. Results are interpreted using simplified models and exclude masses up to 900 GeV for electroweakinos, 1550 GeV for squarks, and 2250 GeV for gluinos.

New reaction approach to reflect exotic structure of hadronic molecular state

With the accumulation of experimental data, more and more exotic hadrons are observed. Among the interpretations of these exotic hadrons, molecular state and compact multiquark are two of the most popular pictures. However, it is still difficult to determine the structure of an exotic hadron. In this work, we propose a possible way to detect the internal structure of an exotic state. When a molecular state composed of two consistent hadrons is attacked by another particle, one of the constituents should be kicked out while another quasifree constituent stays almost unaffected. It is different from a compact multiquark which has no obvious subcluster. In this work, taking the $X(3872)$ as an example, we perform a Dalitz plot analysis of such reaction to find the effect of the different internal structures. Under the assumption of the $X(3872)$ as a molecular state or a compact tetraquark state, with the help of the effective Lagrangians, the Dalitz plot and the invariant mass spectrum are estimated with different total invariant mass of three final particles, and the effect of different binding energies is also discussed. Obvious event concentration can be observed as strips in the Dalitz plot and sharp peaks in the invariant mass spectrum for the $X(3872)$ with a small binding energy under the molecular state picture, while such concentration cannot be observed under the compact tetraquark picture. Such phenomenon can be applied to identify the internal structure of a new hadron state.

Denovo-GCN: De Novo Peptide Sequencing by Graph Convolutional Neural Networks

The de novo peptide-sequencing method can be used to directly infer the peptide sequence from a tandem mass spectrum. It has the advantage of not relying on protein databases and plays a key role in the determination of the protein sequences of unknown species, monoclonal antibodies, and cancer neoantigens. In this paper, we propose a method based on graph convolutional neural networks and convolutional neural networks, Denovo-GCN, for de novo peptide sequencing. We constructed an undirected graph based on the mass difference between the spectral peaks in a tandem mass spectrum. The features of the nodes on the spectrum graph, which represent the spectral peaks, were the matching information of the peptide sequence and the mass spectrum. Next, the Denovo-GCN used CNN to extract the features of the nodes. The correlation between the nodes was represented by an adjacency matrix, which aggregated the features of neighboring nodes. Denovo-GCN provides a complete end-to-end training and prediction framework to sequence patterns of peptides. Our experiments on various data sets from different species show that Denovo-GCN outperforms DeepNovo with a relative improvement of 13.7–25.5% in terms of the peptide-level recall.

The isotope distribution: A rose with thorns.

The isotope distribution, which reflects the number and probabilities of occurrence of different isotopologues of a molecule, can be theoretically calculated. With the current generation of (ultra)-high-resolution mass spectrometers, the isotope distribution of molecules can be measured with high sensitivity, resolution, and mass accuracy. However, the observed isotope distribution can differ substantially from the expected isotope distribution. Although differences between the observed and expected isotope distribution can complicate the analysis and interpretation of mass spectral data, they can be helpful in a number of specific applications. These applications include, yet are not limited to, the identification of peptides in proteomics, elucidation of the elemental composition of small organic molecules and metabolites, as well as wading through peaks in mass spectra of complex bioorganic mixtures such as petroleum and humus. In this review, we give a nonexhaustive overview of factors that have an impact on the observed isotope distribution, such as elemental isotope deviations, ion sampling, ion interactions, electronic noise and dephasing, centroiding, and apodization. These factors occur at different stages of obtaining the isotope distribution: during the collection of the sample, during the ionization and intake of a molecule in a mass spectrometer, during the mass separation and detection of ionized molecules, and during signal processing.

Stochastic assembly of biomacromolecular complexes: impact and implications on charge interpretation in native mass spectrometry.

Native mass spectrometry is a potent method for characterizing biomacromolecular assemblies. A critical aspect to extracting accurate mass information is the correct inference of the ion ensemble charge states. While a variety of experimental strategies and algorithms have been developed to facilitate this, virtually all approaches rely on the implicit assumption that any peaks in a native mass spectrum can be directly attributed to an underlying charge state distribution. Here, we demonstrate that this paradigm breaks down for several types of macromolecular protein complexes due to the intrinsic heterogeneity induced by the stochastic nature of their assembly. Utilizing several protein assemblies of adeno-associated virus capsids and ferritin, we demonstrate that these particles can produce a variety of unexpected spectral appearances, some of which appear superficially similar to a resolved charge state distribution. When interpreted using conventional charge inference strategies, these distorted spectra can lead to substantial errors in the calculated mass (up to ∼5%). We provide a novel analytical framework to interpret and extract mass information from these spectra by combining high-resolution native mass spectrometry, single particle Orbitrap-based charge detection mass spectrometry, and sophisticated spectral simulations based on a stochastic assembly model. We uncover that these mass spectra are extremely sensitive to not only mass heterogeneity within the subunits, but also to the magnitude and width of their charge state distributions. As we postulate that many protein complexes assemble stochastically, this framework provides a generalizable solution, further extending the usability of native mass spectrometry in the characterization of biomacromolecular assemblies.

Resolution and Resolving Power in Mass Spectrometry.

The term resolution is one of the most important in mass spectrometry because it describes the ability to separate peaks in mass spectra. The term resolving power is often used to describe the ability of a mass spectrometer to resolve adjacent peaks in a mass spectrum and is often used interchangeably with resolution. The separation of peaks for singly charged ions can be expressed as a mass difference Δm and the ratio m/Δm is often given as a quantitative measure of the ability of a mass spectrometer to separate ions. Over the past 50 years, several definitions of mass resolution and mass resolving power have been recommended both by the International Union for Pure and Applied Chemistry and the American Society for Mass Spectrometry that define both resolution or resolving power as m/Δm which has led to confusion about the proper use of these terms. The goal of this work is to investigate the origins and use as well as prior and current definitions of resolution and resolving power and make recommendations for the definition of these terms.

Isolation and Purification of the Anti-Bacterial Compound of Cinnamon Oil Extracted from South India

Cinnamon oil is derived from the leaves of the cinnamon tree, the essential oil of the plant is extracted by steam distillation, while its bark is used to make cinnamon spice. The present study was conducted to isolate the most important bioactive compounds from cinnamon oil extracted from South India. The thin-layer chromatography (TLC) combined with high-performance liquid chromatography (HPLC) were used to determine and estimate the isolates obtained. It found that the organic phase's highest retention time was 5.433, and the peak area percentage was 88.8 %. The organic phase sample had a high peak area percentage, indicating that there was a lot of bioactive chemical in it. The broad absorption band at 3270 cm-1 is due to the (-OH) group, 1670 and 1623 cm-1 to the C=C group, 1449 and 1381 cm-1 to the (-C-H) group, and the band at 1120 cm-1 to the (-C-O) group. A pseudo molecular ion peak at m/z 275 for a [M+H] +. This study resulted in finding a peak in the positive mode mass spectra, indicating a molecular weight of 274 and the molecular formula of C15H14O5.1H 13CNMR investigations verified the presence of phenol hydroxide groups, two aromatic ring systems, methylene groups, and a phenoxy carbon in the chemical composition of the compound. Moreover, the composition is quite similar to catechins, and this chemical is separated from the organic phase of cinnamon oil. The potent inhibitory activity of the newly synthesized catechin antagonist against S.aureus and E.coli was found to assess cell death by detection of DNA fragments using agarose gel electrophoresis and SEM analysis.

A simple soft ionization approach for GC-MS assisted by capillary array

Electron ionization (EI) is the most widely used ionization method in gas chromatography/mass spectrometry (GC-MS). This method possesses a lot of advantages including versatility for various classes of volatile and semi volatile organic compounds, high sensitivity, structure informativity and reproducibility, production of database searchable mass spectra. On the other hand there are a number of compounds, which molecular ions are not stable enough to produce corresponding peaks in EI mass spectra, making it difficult to determine structures of compounds not presented in databases. A new approach allowing easy implementation of EI in a molecular beam formed by a capillary assembly is proposed for discussion in this communication. Primary experimental results achieved using this approach demonstrate its possibility to produce suitable for database search mass spectra with increased intensity of molecular ion peak.

Study of LEAP® 5000 Deadtime and Precision via Silicon Pre-Sharpened-Microtip™ Standard Specimens.

Atom probe tomography (APT) is a technique that has expanded significantly in terms of adoption, dataset size, and quality during the past 15 years. The sophistication used to ensure ultimate analysis precision has not kept pace. The earliest APT datasets were small enough that deadtime and background considerations for processing mass spectrum peaks were secondary. Today, datasets can reach beyond a billion atoms so that high precision data processing procedures and corrections need to be considered to attain reliable accuracy at the parts-per-million level. This paper considers options for mass spectrum ranging, deadtime corrections, and error propagation as applied to an extrinsic-silicon standard specimen to attain agreement for silicon isotopic fraction measurements across multiple instruments, instrument types, and acquisition conditions. Precision consistent with those predicted by counting statistics is attained showing agreement in silicon isotope fraction measurements across multiple instruments, instrument platforms, and analysis conditions.

Mass spectral and theoretical investigations of N-Cα bond cleavages in the disulfide-containing peptide TTCPYCKK and its analogues.

For disulfide-containing peptides, mass spectrometric analyses are rarely comparably studied between their dithiol and disulfide forms. Persulfide ions afforded from peptides with a disulfide ring are from either an unusual N-Cα bond cleavage or a canonical peptide bond cleavage; their isomeric structures are, however, not identified just from peaks of mass spectra. Isomeric structures of [C3 P4 X5 |C6 M ], [C3 MA P4 X5 |C6 MB ] and [P4 X5 C6 |C3 M ] were identified from a series of the X5 substituted dicysteine octapeptides using electrospray ionization tandem mass spectrometry for both their dithiol and disulfide forms. Formation mechanisms of different persulfide ions were investigated systematically by theoretical methods. Moreover, electrostatic potential-mapped molecular van der Waals surfaces were used to determine the stabilities of the intermediates, which gave a further evaluation of favored bond cleavage. Mass spectral analyses indicated that the fragmented ions changed largely when an intramolecular disulfide bond was formed. New types of disulfide-containing fragmented ions [C3 P4 X5 |C6 M ] or [C3 MA P4 X5 |C6 MB ] were thus proposed. Energy analysis showed that the N-Cα cleavage was not competitive energetically with that of the amide bond for Y5 and its phosphorylated analogue. However, the N-Cα cleavage products dominated for the S5 - and T5 -containing peptides. Stabilities of the intermediates were found to be related with the electrostatic potential-mapped molecular van der Waals surfaces. Persulfide ions containing more residues than previously found were proposed not only from b7 ions but also from y6 ions. In addition, a new kind of phosphorylated analogue, [C3 P4 p Y5 |C6 M ], is reported in this work. Our study provides convincing results for separating isomeric structures in the cases of N-Cα cleavages, which greatly assists in the structural identification of disulfide-containing peptides.

GC–MS and GC–IR of regioisomeric 4-N-bromodimethoxybenzyl derivatives of 3-trifluoromethylphenylpiperazine

The seven regioisomeric N-bromodimethoxybenzyl derivatives of 3-TFMPP were synthesized via reductive amination of the seven commercially available bromodimethoxybenzaldehydes. The capillary GC elution profiles for these compounds generally follow the degree of methoxy group substituent crowding on the aromatic ring. The electron ionization mass spectra show a series of major fragment ions common to all seven regioisomeric compounds. The base peak in the EI mass spectra for many of the seven regioisomers occurs at m/z 229 and is the result of contributions from two isobaric fragments, the trifluoromethylphenylpiperazine cation as well as the 79Br bromodimethoxybenzyl cation. Several low intensity ions are related to the specific regioisomeric substitution patterns for the bromodimethoxybenzyl moieties and provide some differentiation for this set of seven compounds. These unique ions allow the seven compounds to be divided into sub-groups and in some cases allow specific isomer identification from only the EI-MS data. The 950 cm−1 to 550 cm−1 lower portion of the fingerprint region in the vapor phase infrared spectra can be used to identify each of the bromodimethoxybenzyl regioisomers after EI-MS fragmentation patterns provide focus on the individual structural sub-groups of compounds in this study.

High-performance nontarget analysis of halogenated organic compounds in tap water, fly ash, soil and sediment using ultrahigh resolution mass spectrometry and scripting approaches based on Cl/Br-specific search algorithms

Halogenated organic compounds (HOCs) are a huge group of pollutants, which have caused severe environmental pollution worldwide. This study developed a nontarget analysis method for characterization of known and unknown HOCs in tap water, fly ash, soil and sediment using Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR-MS) with aid of scripting data-processing approaches. The FT-ICR-MS was equipped with an electrospray ionization source operated in negative ion mode, and full scan at a mass resolution around 200,000 was applied. Data screening scripts were developed based on exact mass differences and abundance ratios between neighboring chlorine/bromine isotopologues. Cosine similarity analysis was applied to evaluating similarity between measured and simulated isotopologue distributions which were constituted by abundance ratios between neighboring isotopologues for identification of polychlorinated and polybrominated compounds. From huge amount of peaks in raw mass spectra, thousands of MS features of HOCs were screened out. In total 824 HOC formulae were finally identified, including 702 organochlorines, 108 organobromines, and 14 mix-chlorine/bromine-containing organic compounds (OClBrs), mainly being monochlorinated/monobrominated compounds (∼90%) whose abundances were also the most prominent. Dozens of HOCs were tentatively structurally elucidated, including halogenated phenols, carboxylic acids, benzenesulfonic acids, etc. Three novel OClBrs were structurally identified, i.e., bromochlorobenzoic acid, bromodichlorophenol and bromotrichlorophenol. The data-processing scripts and strategies can facilitate accurate and high-throughput nontarget analysis of both common and novel/emerging halogenated organic pollutants in complex matrices. The research results provide informative insights into pollution profiles of HOCs in the environment, suggesting that halogenated organic pollutants remain to be seriously concerned.

Mass Defect Filter for Removing Noise and Detector Oscillation Artifacts in Centroided Time-of-Flight Mass Spectra.

Spurious peaks in centroided mass spectra resulting from detector oscillation or "ringing" can be identified by their unusual mass defects. Mass defect plots (fractional m/z vs measured m/z) for the single-charge mass spectrum of a pure compound show data points falling along lines with well-defined slopes. Detector oscillation and electronic noise peaks were removed from database spectra of pure compounds and mixtures by eliminating points outside two standard deviations of the slope of the major peaks. No loss of chemical information was observed, even for compounds with isobaric fragment peaks.