Journal of the American Society for Mass Spectrometry最新文献

This study introduces an alternative strategy for evaluating antiparasitic persistence compounds in cattle hair by Direct Analysis in Real Time Mass Spectrometry (DART-MS). The developed DART-MS method aimed to determine fenthion, chlorpyrifos, and cypermethrin in cattle hair samples. DART-MS analyses were performed in positive ion mode, and parameters related to the DART source were evaluated. The analytical performance demonstrated the efficiency of the optimized DART-MS method for fenthion, chlorpyrifos, and cypermethrin quantification in the evaluated samples, meeting criteria for precision, accuracy and limits of detection. Overall, the DART-MS method provided a fast and efficient analysis for determination of antiparasitic agents in cattle hair, which contributes to the evaluation of drug administration protocols and dosage intervals, and aids the safety and advancement of the livestock sector.

Peak annotation plays an important role in mass spectral evaluation of the NIST 2023 tandem mass spectral library. While most fragment ions are formed by neutral losses, there are peaks that represent adduct ions from these fragments. Previously, we have reported two main types of addition reactions in the collision cell, namely addition of H₂O and N₂. Here we report a different reaction in the collision cell, with addition of O₂ leading to a small peak that could only be assigned to a peroxyl radical ion. For example, some protonated iodoaromatics lose an iodine atom to form a radical cation [M+H-I]^+•, which reacts with O₂ to generate a peroxyl radical ion [M+H-I+O₂]^+•. Higher concentrations of O₂ result in higher peroxyl radical peaks, which become dominant while the precursor ions are consumed, as examined by five compounds under different concentrations of O₂. The correlation of the peroxyl radical peak intensities to the concentration of O₂ provides a tool to estimate trace amounts of O₂ within the instrument. In the NIST 2023 tandem mass spectral library, the peaks for [M+H-X+O₂]^+· are most abundant in numbers and in intensity for X = NO₂ or I, are much less abundant for X = Br, and are rare for X = Cl. Other leaving groups in this library are SO₃H, SO₂NH₂, CSNH₂, CO₂C₆F₅, SO₂CH₃, and COCH₃. The O₂ addition reaction is also observed with negative ions in this library. While adducts of H₂O and N₂ often constitute major peaks, the peaks of the peroxyl radicals under standard conditions are mostly very small and may be mistaken for noise, but their correct annotation improves the quality of the spectra and is important when comparing spectra from different instruments or conditions.

Mass spectrometry imaging (MSI) techniques enable the generation of molecular maps from complex and heterogeneous matrices. A burger patty, whether plant-based or meat-based, represents one such complex matrix where studying the spatial distribution of components can unveil crucial features relevant to the consumer experience or production process. Furthermore, the MSI data can aid in the classification of ingredients and composition. Thin sections of different burger samples and vegetable constituents (carrot, pea, pepper, onion, and corn) were prepared for matrix-assisted laser desorption/ionization (MALDI) and desorption electrospray ionization (DESI) MSI analysis. MSI measurements were performed on all samples, and the data sets were processed to build three machine learning models aimed at detecting meat adulteration in vegetable burger samples, identifying individual ingredients within the vegetable burger matrix, and discriminating between burgers from different manufacturers. Ultimately, the successful detection of adulteration and differentiation of various burger recipes and their constituent ingredients were achieved. This study demonstrates the potential of MSI coupled with building machine learning models to enable the comprehensive characterization of burgers, addressing critical concerns for both the food industry and consumers.

Cold EI improves all of the central GC-MS performance aspects, but even though it is known for providing enhanced molecular ions, it is important to realize that Cold EI mass spectra also include all of the standard EI fragment ions. Thus, Cold EI mass spectra are fully compatible with mass spectral libraries, such as NIST for sample identification. As a result, Cold EI mass spectra (unlike any other soft ionization method) provide highly effective identifications that are often better than those obtained with standard EI for a few reasons:1).Cold EI mass spectra with enhanced molecular ions typically provide higher identification probabilities than standard EI, even though scoring lower matching factors (false alternatives scores are lowered much more).2).The visually observed molecular ions further serve to confirm or reject the NIST library identifications.3).Molecular ions provide isotope abundances that serve with our TAMI software for automatic confirmation or rejection of the NIST library identification and provide an elemental formula in case the compound is not in the library.4).The Cold EI identification probability can be even higher than that of a mass spectrum with a perfect match of 999 that can be obtained by NIST library searching its own mass spectrum.5).The clear Cold EI molecular ion enables the use of the NIST library option of constraints search with the molecular ion that further significantly increases the identification probability. Our findings are demonstrated with mass spectra of hexadecane (n-C₁₆H₃₄), n-C₄₀H₈₂, pyrene, nitrobenzene, chlorpromazine, di-n-octyl phthalate, and deltamethrin.

The thermal decomposition of per- and poly fluoroalkyl substances (PFAS) is poorly understood. Here, we present an innovative, comprehensive analytical method to investigate their thermal decomposition, including perfluorocarboxylic acids (PFCAs), alcohol, sulfonates, and GenX (acid dimer), focusing on identifying their breakdown products. In this study, evolved gas analysis-mass spectrometry (EGA-MS) was used for fast real-time screening to determine the significant temperatures to be investigated with the thermal desorption-pyrolysis coupled with gas chromatography-mass spectrometry (TD-Py-GC-MS), which provided detailed information about evolved PFAS and their breakdown products. This approach enabled a systematic study of perfluorocarboxylic acids (PFCAs) ranging from C₃ to C₉ and GenX showing volatilization, followed by degradation and formation of respective perfluorinated-1-alkenes and C₅F₁₀O perfluorinated ether (from GenX). At elevated temperatures (e.g., 600 °C), the products observed included perfluorinated butene and higher molecular-weight products, likely formed by pyrolytic polymerization of perfluorinated radicals. 1H,1H,2H,2H-perfluoro-1-decanol, i.e., 8:2 FTOH, volatilized at 100 °C; however, at higher temperatures, several novel decomposition products were observed, including perfluoro-1-decene and perfluorinated compounds suggesting the presence of the hydroxylic group. Our method offers an alternative approach to studying the thermal behavior of currently regulated and emerging PFAS with a focus on application to a wide range of matrices (laboratory grade standards or environmental samples).

This Perspective explores the transformative impact of ultrahigh-resolution mass spectrometry (UHR-MS), particularly Fourier transform ion cyclotron resonance (FT-ICR-MS), in the characterization of complex environmental and petroleum samples. UHR-MS has significantly advanced our ability to identify molecular formulas in complex mixtures, revolutionizing the study of biogeochemical processes and organic matter evolution on wide time scales. We start by briefly reviewing the main technological advances of UHR-MS in the context of petroleum and environmental applications, highlighting some of the challenges of the technology such as quantitation and structural identification. We then showcase a selection of impactful applications published in the last 20+ years. In the field of environmental lipidomics, high-resolution analysis of lipids in sediments enables multiproxy studies and provides novel insights into past environmental conditions. UHR-MS has also facilitated the characterization of kerogen, a complex, poorly soluble mixture formed from sedimented organic matter over geological time scales, and the identification of polar compounds within its fractions. In petroleum (geo)chemistry, UHR-MS has enabled the identification of biomarkers such as petroporphyrins, asphaltenes, and high-molecular-weight naphthenic acids, shedding light on the molecular complexity of crude oil. The application of UHR-MS in oil spill science has revealed significant molecular transformations during weathering processes, such as photo-oxidation, which are crucial for assessing the environmental impact of past spills and improving the preparedness for future spills. These advancements underscore the role of this maturing analytical technology in deepening our understanding of geochemical processes and biogeochemical cycles, highlighting its potential for future research directions in organic geochemistry.

Imaging mass spectrometry (IMS) is a technique for simultaneously acquiring the expression and distribution of molecules on the surface of a sample, and it plays a crucial role in spatial omics research. In IMS, the time cost and instrument load required for large data sets must be considered, as IMS typically involves tens of thousands of pixels or more. In this study, we developed a high-resolution method for IMS data reconstruction using a window-based Adversarial Autoencoder (AAE) method. We acquired IMS data from partial cerebellum regions of mice with a pitch size of 75 μm and then down-sampled the data to a pitch size of 150 μm, selecting 22 m/z peak intensity values per pixel. We established an AAE model to generate three pixels from the surrounding nine pixels within a window to reconstruct the image data at a pitch size of 75 μm. Compared with two alternative interpolation methods, Bilinear and Bicubic interpolation, our window-based AAE model demonstrated superior performance on image evaluation metrics for the validation data sets. A similar model was constructed for larger mouse kidney tissues, where the AAE model achieved high image evaluation metrics. Our method is expected to be valuable for IMS measurements of large animal organs across extensive areas.

Peptide conjugates furnished with a 2,5-diaryltetrazolecarbonyl tag at the C-terminal lysine, which we call peptide-tet-K, were found to undergo efficient cross-linking of Asp, Glu, Asn, and Gln residues to transient nitrile-imine intermediates produced by photodissociation and collision-induced dissociation (CID) of the tetrazole ring in gas-phase ions. UV photodissociation (UVPD) at 213 nm achieved cross-linking conversion yields of 37 and 61% for DAAAK-tet-K and EAAAK-tet-K, respectively. The yields for NAAAK-tet-K and QAAAK-tet-K were 29 and 57%, respectively. Even higher cross-link yields were found for CID-MS³ of stable denitrogenated ions, (peptide-tet-K-N₂ + H)⁺, that were in the 69-83% range. Different types of cross-links were distinguished by CID-MSⁿ that showed a distinct series of backbone fragment ions, loss of N-terminal groups, and loss of phenylhydrazine from the modified nitrile imines. The Asp and Glu side-chain carboxyl groups were major participants in cross-linking that resulted in proton and oxygen transfer to the nitrile imine group. Other types of cross-linking involved Asn and Gln CONH₂ groups and backbone amides. Cyclic ion mobility-mass spectrometry was used to separate NAAAK-tet-K and QAAAK-tet-K conformers and products of their collision-induced denitrogenation. Linear nitrile-imine and cross-linked ion structures were identified by comparing the experimental collision cross sections (CCS_exp) to those for structures obtained by combined Born-Oppenheimer molecular dynamics and density functional theory (DFT) calculations. The formation of cross-links was found to be energetically favorable and involved proton-facilitated nucleophilic attack at the nitrile-imine carbon atom.

Native mass spectrometry analysis of proteins directly from tissues can be performed by using nanospray-desorption electrospray ionization (nano-DESI). Typically, supplementary collisional activation is essential to decluster protein complex ions from solvent, salt, detergent, and lipid clusters that comprise the ion beam. As an alternative, we have implemented declustering by infrared (IR) photoactivation on a linear ion trap mass spectrometer equipped with a CO₂ laser (λ = 10.6 μm). The prototype system demonstrates declustering of intact protein complex ions up to approximately 50 kDa in molecular weight that were sampled directly from brain and eye lens tissues by nano-DESI. For example, signals for different metal binding states of hSOD1^G93A homodimers (approximately 32 kDa) separated by only approximately 6 Th (10+ ions) were resolved with IR declustering, but not with collisional activation. We found IR declustering to outperform collisional activation in its ability to reduce chemical background attributable to nonspecific clusters in the nano-DESI ion beam. The prototype system also demonstrates in situ native MS on a low-cost mass spectrometer and the potential of linear ion trap mass spectrometers for this type of analysis.