Journal of the American Society for Mass Spectrometry最新文献

The protonation site of a molecule can significantly influence its gas-phase behavior and fragmentation, especially when multiple protonation sites are accessible. Here, we characterize two gas-phase protonation site isomers (hereafter referred to as protomers) of quizartinib using cyclic ion mobility–mass spectrometry (cIMS-MS), tandem MS, and molecular modeling. Despite density functional theory (DFT) calculations indicating a gas-phase preference for protonation at the central imidazole nitrogen (hereafter N21), two mobility-separated species were observed, suggesting kinetic trapping of a solution-phase protomer. To probe this hypothesis, solvent-phase molecular modeling using implicit water and acetonitrile models was performed, revealing that the morpholine nitrogen (hereafter N15) is the most favorable protonation site in solution. This supports a dual-phase model: one protomer arises from the liquid-phase favored protonation site, and the other from the gas-phase protonation site. Post-IMS fragmentation of the protomers revealed a common m/z 421 product ion, along with other shared fragments at m/z 395 and m/z 114. Product ion m/z 308 was unique to protomer 1, while m/z 334, m/z 307, m/z 281,276 and m/z 87 were unique to protomer 2. To investigate the origins of m/z 421 and m/z 395, these ions were generated by pre-IMS activation, isolated, and subjected to cIMS separation. Both ions exhibited two distinct arrival time peaks, indicating that they retain the protonation-site memory of their precursors. The two mobility-separated m/z 421 ions further yielded unique as well as some common fragments upon dissociation. We propose a charge remote hydrogen transfer mechanism for formation of m/z 421 and m/z 395, initiated from either the morpholine (N15) or imidazole (N21) protonation. Structural assignments were proposed for the major common and unique product ions of each protomer. These findings highlight a mechanistic link between solution- and gas-phase protonation and demonstrate the utility of cIMS-MS for probing structure-specific fragmentation and isobaric dissociation product ion resolution in small molecules with multiple heteroatoms.

In mass spectrometry (MS), the radio frequency (RF)-only multipole ion guide commonly used in a medium pressure range (0.1–10 Pa) is susceptible to a collision-damping-induced loss of instrumentation sensitivity, resulting in operation within a limited m/z bandwidth. In this study, a novel direct current (DC)-free gradient-threaded discrete twisted dipole ion guide (GTDIG) is proposed for high-efficiency ion propulsion and an expanded m/z bandwidth in a medium vacuum (0.1–10 Pa). An overview of the GTDIG working principles is provided with systematic optimization of the critical parameters. The GTDIG has been applied by using a series of printed circuit boards, utilizing an innovative discrete helical electrode design. The performance of the GTDIG prototype is evaluated using multiphysical numerical modeling and tested using a custom-built nanoelectrospray ionization (ESI)-MS platform, including a direct comparison with a quadrupole ion guide. The results indicate that the RF-only GTDIG offers a significantly larger m/z window while effectively maintaining an axial field, demonstrating that this concept can be utilized in the development of instruments with an enhanced performance.

Desorption electrospray ionization mass spectrometry (DESI-MS) imaging is a well-established technique for molecular analysis of biological samples, although its spatial resolution has been limited when compared to other MS imaging techniques. Here, we describe the development and optimization of a low-flow DESI-MS method that allows for sub-10 μm spatial resolution tissue imaging using a commercial DESI sprayer. Key technical modifications that enabled low-flow high-resolution DESI-MS imaging include reduced solvent flow rates below 350 nL/min, increased solvent pump back-pressure for spray stability, and optimized sprayer design and geometry. We applied low-flow DESI to image porcine liver and rat brain tissue sections at a spatial resolution of 5–10 μm, and the resulting ion images showed high spatial fidelity and detailed tissue histologic features. Building on the nondestructive nature of DESI-MS, we demonstrate that a tissue section can be first imaged with low-flow DESI at lower resolution (100–200 μm pixel size), followed by high-resolution (5–10 μm pixel size) imaging of selected regions of interest in the same tissue section. Lastly, we applied low-flow DESI to image and classify human thyroid cancer tissue sections and fine-needle aspiration (FNA) biopsies at 10 μm spatial resolution, achieving accurate identification of cancer cells in the FNA sample. Altogether, these results demonstrate the robustness and applicability of low-flow DESI-MS for high spatial resolution imaging of tissue sections, which could in the future potentially be implemented across a variety of biomedical and clinical studies.

In order to transport ions from an intermediate-pressure collisional cooling device to a planar electrostatic ion trap (PEIT) mass analyzer in an ultrahigh-vacuum chamber, a segmented radio frequency (RF) quadrupole system was designed and investigated by using an ion optical simulation. Two gas-flow-limiting units were employed in the system, allowing the differential pumping to establish a pressure difference of 7 orders of magnitude. Flow-limiting units including a plain aperture lens and 3 small quadrupoles in different shapes were investigated, and the transmission efficiency and energy distribution of the transported ions were evaluated. The small quadrupoles with conical front-ends inserted between the multiple segments gave the best transmission efficiency, and the collisional cooled ions can maintain their low energy distribution after being transported to the ultrahigh-vacuum stage. With an RF voltage amplitude of 200 V, the maximum transmission efficiency reached above 90%. After ions are cooled in the high-pressure quadrupole segment, the extraction voltage difference in high-pressure region needs to be low enough to avoid reheating the ions during the transport. It was found that an extraction voltage difference below 1.2 V can restrict the half width of the energy spread within 0.5 eV, which is required by PEIT to get ultrahigh mass resolution.

Molecular networking is a computational mass spectrometry technique used to visualize and connect tandem mass spectra from putatively related molecules to reveal structural relationships. Despite their utility, existing tools for interpreting molecular networks are limited in the ability to easily organize fragmentation patterns within molecular families. We developed an interactive web-based tool, the Multiple Mass Spectral Alignment (MMSA) approach, that enhances the visualization of molecular networks by displaying detailed spectral alignment information among all the spectra in a network component in one visualization. MMSA identifies sets of consensus peaks that contribute to the alignment of multiple tandem mass spectra, offering insights into how structural moieties captured by specific fragments influence the construction of molecular networks. We demonstrate that MMSA facilitates insightful understanding of molecular networks and improves the interpretability of the tandem mass spectra, capturing the chemical modifications or core structures within a molecular family. We envision that the MMSA tool will significantly enhance the ability to interpret molecular networks, with implications for more rapid identification and prioritization of new metabolites for full characterization.

Loss of hydrophobic peptides and proteins remains a significant challenge in bottom-up proteomics, resulting in under-representation of membrane and membrane-associated proteins that are critical for understanding cellular function and disease. This limitation is particularly acute for targeted applications such as S-palmitoylation analysis, where modifications occur preferentially on membrane-proximal cysteines. This study evaluated supplementation by n-dodecyl-β-d-maltopyranoside (DDM), a mild detergent widely used in structural biology but not proteomics, during the postprecipitation resolubilization step to enhance hydrophobic protein recovery. Using immortalized bone marrow-derived macrophages (iBMDMs), we compared standard resolubilization (8 M urea in 50 mM ammonium bicarbonate) with DDM-supplemented conditions. In global proteomics, DDM supplementation improved peptide and protein identifications, with particularly pronounced benefits for membrane protein recovery. The 539 proteins uniquely identified with DDM were enriched for mitochondrial components, protein complexes, and membrane-bounded organelles. For acyl-biotin exchange (ABE) proteomics targeting palmitoylated proteins, DDM supplementation enhanced recovery of proteins, with 223 proteins consistently requiring DDM for identification. These DDM-dependent proteins showed enrichment for transport and localization functions characteristic of palmitoylated proteins. Comparison with the SwissPalm database revealed 336 previously unreported S-palmitoylation candidates, with DDM conditions contributing more novel identifications than urea alone. These findings demonstrate that DDM-assisted resolubilization addresses a key bottleneck in proteomics workflows, enabling more comprehensive characterization of hydrophobic and lipid-modified proteomes without requiring extensive protocol modifications.

Matrix-assisted laser desorption electrospray ionization (MALDESI) enables mass spectrometry imaging (MSI) capabilities to reveal the localization of a wide range of biomolecules across an organism. Three-dimensional (3D) MSI of biological tissues is typically accomplished by imaging two-dimensional sections followed by the creation of a 3D image informatically. In contrast to this sectioning-based approach, we employ an ablation-based 3D MSI technique to image Artemisia annua, a medicinal herb that naturally produces the antimalarial drug artemisinin. We incorporated a novel high-energy burst-mode ultraviolet (UV) laser, and a chromatic confocal aberration (CA) probe with automatic z-axis correction (AzC) to measure the depth of ablation (i.e., z-resolution). The combination of these techniques allowed the visualization of the artemisinin metabolic pathway along with other secondary metabolites beneath the tissue surface, as supported by the resulting data. This approach enabled detailed molecular mapping in 3D, providing a comprehensive view of the plant’s molecular landscape layer by layer, offering new insights into its biosynthetic pathways in three dimensions.

Plant metabolomics faces major challenges in metabolite identification due to the structural diversity of plant metabolites and limited coverage in existing spectral libraries. To address this, we developed CIeaD (Collision-Induced and Electron-Activated Dissociation), an open-access plant metabolite spectral library containing complementary CID and EAD spectra. The library includes curated high-resolution spectra for 2,305 phytochemicals across major metabolite classes, acquired in both positive and negative modes with a dual fragmentation mechanism to capture a wide range of diagnostic ions. CIeaD library is provided in multiple formats and can be accessed at https://www.moleculardetective.org/Links.html.

Proteogenomics integrates genomics and mass spectrometry (MS) data to understand complex biological systems, disease mechanisms, and potential biomarkers. However, the high volume and noise in MS data present computational and interpretational challenges in proteogenomic studies where, despite best efforts, many spectra are often left unassigned. We developed SpecQuality, an easy-to-use tool for MS/MS quality assessment. We evaluated ten spectral features and, using the top features, developed a machine learning-based model to predict the quality of MS/MS spectra through a spectral quality score (SQS). SpecQuality can be used prior to database search or for postsearch validation of peptide spectrum matches (PSMs). This enables rapid prioritization of high-quality PSMs from proteomics and proteogenomics searches, thereby reducing false-positive identifications. We demonstrated its utility in proteogenomics applications by evaluating its performance on two data sets with ∼2.7 million spectra from Alzheimer’s disease, where it successfully highlighted high quality spectra. The spectra that matched novel, variant, and modified peptides in the proteogenomics search were observed to be of high spectral quality. Additionally, a direct comparison with manually curated variant identifications demonstrated its capacity to mitigate false positives and enhance reliability. SpecQuality is an open-source, freely available, easy-to-use, simple, and versatile tool developed in both Python and Perl that can be leveraged in many proteomics pipelines. It can be easily used as a standalone tool or integrated as a part of a bioinformatics data analysis pipeline. SpecQuality provides a scalable and accessible approach to spectral prioritization, advancing data integrity in proteomics and proteogenomics. SpecQuality is available at https://github.com/alkayadav10/SpecQuality.