Combining HDX-MS and NMR enables the mapping of epitopes and paratopes in full-length antibody complexes, revealing transient interactions and potential artifacts. ABSTRACT Recombinant biomacromolecules have significantly transformed pharmaceuticals, in particular monoclonal antibodies (mAbs) that target key areas in oncology, immunology, inflammation, and neurodegenerative diseases. Developing biotherapeutics requires a detailed understanding of their biological properties. This, in turn, brings about the importance of characterizing higher-order protein structures at each stage, from production to patient. The flexibility and size of the mAbs often prevent achieving atomic-level structural information in the pharmaceutical formulation by traditional methods. In this study, we introduce an integration of solid-state nuclear magnetic resonance (SSNMR) and hydrogen–deuterium exchange mass spectrometry (HDX-MS) to explore the interaction between Avelumab and the programmed cell death-ligand 1 (PD-L1). With this approach, we were able to obtain epitope (by both NMR and HDX) and paratope mapping (by HDX), together with a detailed characterization of the structural rearrangements arising upon binding. This methodology provides both mechanistic and structural insights important for the design and optimization of biotherapeutics.

Publication date: November–December 2026 Source: International Journal of Mass Spectrometry, Volumes 529–530 Author(s):

Publication date: November–December 2026 Source: International Journal of Mass Spectrometry, Volumes 529–530 Author(s):

Publication date: Available online 10 October 2026 Source: International Journal of Mass Spectrometry Author(s): Pongpanot Pongworasuwanna, Giel Berden, Jos Oomens, Caroline E.H. Dessent, Sarah A. Wilson

AbstractWith the rapid development of mass spectrometry-based proteomics, the volume of phosphoproteomic data has increased substantially. However, accurate localization of phosphorylation sites and standardized statistical validation remain critical analytical bottlenecks. To address the lack of standardized cross-algorithm evaluation, we introduce onsite, a unified and open-source Python framework. onsite integrates an alanine-decoy strategy to estimate the false localization rate (FLR) across three algorithms: AScore, PhosphoRS, and pyLucXor. This modular architecture efficiently processes large-scale data sets and enables global FLR calculation. Benchmarking on the standard synthetic phosphopeptide data set PXD000138 highlighted distinct interalgorithmic variations. Using the same 5% global FLR threshold, pyLucXor localized the most target sites (28,353). It also reached a high accuracy (91.22%) against the known ground truth, resulting in the largest number of correctly localized sites (25,865). Reanalysis of the highly fractionated, large-scale PXD012255 data set further demonstrated that native integration of onsite into the quantms pipeline enables scalable processing and provides a standardized framework for FLR control in large-scale phosphoproteomics.

AbstractMolecular formula (MF) assignment in ultrahigh-resolution mass spectrometry (UHRMS) analyses of dissolved organic matter (DOM) containing multiple non-oxygen heteroatoms (e.g., nitrogen and sulfur) is highly environmentally relevant yet remains challenging. Recent studies of DOM composition in aquaculture systems with protein-rich surface sediments have reported numerous CHNO (N1−8), CHOS (S1−3), and even CHNOS MFs containing multiple N and S atoms, suggesting the presence of oligopeptide-like molecules. Due to insufficient mass resolution, multiple formula assignments (MultiAs) caused by interchangeable replacement pairs, within a mass error threshold of 1 ppm, complicate the validation of MF assignments. While N5S2 formulas are known as likely false-positive assignments of 13C1 isotopologue peaks, the multiple N-containing MFs in MultiAs of potential oligopeptide origins involving replacement pairs with N6 ↔ S1 and S2 ↔ N4 could not be validated properly. Here, we introduce a new chemically informed validation approach based on the elemental composition and stoichiometry of typical peptides with atomic ratios 0.2 < O/C < 0.65 and 1.5 < H/C < 2. Amino acid combinations matched about 36% N-rich MF (n = 960) among N6 ↔ S1 related MultiAs (N7 ↔ N1S1, N8 ↔ N2S1··· N8S2 ↔ N2S3) and 30% N-rich MF (n = 1040) among S2 ↔ N4 related MultiAs (N1S2 ↔ N5, N2S2 ↔ N6···N4S3 ↔ N8S1), supporting the true assignments of N-rich MFs based on oligopeptide stoichiometry. Overall, the chemical complexity of heteroatom-rich DOM warrants advances in MF assignment for UHR mass spectra by expanding the analytical window to include multiple-heteroatom formulas, which would especially benefit protein-rich samples from aquaculture systems or wastewater.

AbstractProteoform-resolved interaction analysis is critical for understanding the functional diversity of multiple proteoforms from the same gene and their complexes. However, current technologies are still limited in resolving in vivo interactions at the proteoform level. In vivo cross-linking followed by bottom-up mass spectrometry (MS) can provide interaction sites but loses proteoform information, whereas top-down MS can characterize proteoform composition but struggles with cross-linked spectral complexity. Herein, we developed a strategy based on tracelessly releasable cross-linking coupled with MS to decipher proteoform-resolved interactions in target protein complexes in living cells. First, we designed a novel cross-linker, bis(N-hydroxysuccinimide) (2,2’-(ethylenebissulfonyl) diethanol) dicarbonate (DSODSE), enabling not only in vivo cross-linking to fix interactions in living cells but also traceless release of cross-linked proteoforms at pH ≥ 8.0 to address the challenges of proteoform identification caused by cross-linking. Benefited from such a cross-linker, an in-depth accurate identification of proteoform components was achieved via in vivo cross-linking, enrichment of target complexes, traceless release, followed by top-down MS. Meanwhile, the cross-linked peptides were analyzed with the identified proteoforms as the database, and the proteoform-resolved interactions were obtained by matching the cross-links to the specific sequence of proteoforms. By this strategy, we deciphered the in vivo proteoform-resolved interaction network of α-syn complexes. To our best knowledge, our work achieves the first delineation of the in vivo proteoform−proteoform interaction network of target protein complexes, providing a powerful tool for understanding the functional diversity of proteoforms and their complexes in living cells.

AbstractIn almost all biological systems, stereochemistry is an important aspect of the molecular structure. Aberrant molecular geometry can be a reflection of the disease state which is then manifested through effects on cellular metabolism. A well-known example occurs in isocitrate dehydrogenase (IDH)-mutant (mut) cancers, where the mutant IDH enzyme produces a unique chiral molecule, d-2-hydroxyglutarate (d-2HG). d-2HG accumulates in IDH-mut tumors and disrupts cellular pathways, including epigenetic regulation. Here, we apply the kinetic method to direct chiral analysis of 2HG in human glioma tissue. A trimeric cluster ion, [Ni(II)(Ac-l-Phe)2(l-2HG)−H]+, is formed and fragmented during tandem mass spectrometry (MS/MS). Cluster ions containing different 2HG geometry show distinctive fragment intensities. Calibration curves spanning from −100% to +100% enantiomeric excess (ee) were constructed, and the effects of potential interferences, including glutamate (Glu) and glutamine (Gln), were assessed. Using these data, we developed a chromatography-free method to determine the ee of 2HG in the glioma tissue. Chiral analysis of IDH-mut glioma tissue samples using the kinetic method was validated using LC−MS, with ee values agreeing within < 12%. Detection of predominantly d-2HG in tissue samples from (IDH)-mutant cancer is consistent with the neomorphic gain of function associated with the IDH mutation. This separation-free workflow enables rapid chiral analysis of 2HG in IDH-mut cancers and may provide complementary information to support intraoperative decision-making and precision medicine applications.

Publication date: Available online 9 October 2026 Source: Journal of Chromatography A Author(s): Toon Verdonck, Christophe Matthys, Patrick Augustijns, Deirdre Cabooter

AbstractPoly(trimethylene ether) glycol (PO3G) is a relevant biobased polyether whose combination of terminal hydroxyl groups and ether linkages enables multiple competing gas-phase dissociation pathways, yet its energy-dependent collision-induced dissociation (CID) remains poorly understood at the mechanistic level. Here, the protonated PO3G dimer (m/z 135) was investigated by energy-resolved mass spectrometry (ERMS) and high-level quantum chemical calculations, focusing on the main first-order fragments at m/z 117, 77, and 59. The lowest energy pathways identified presented barriers of 164.7, 176.7, and 187.3 kJ/mol, respectively, a progression qualitatively consistent with the experimental fragmentation trends. The calculations further suggest that kinetically accessible structures may differ from the thermodynamically most stable products. In particular, a protonated epoxide intermediate provides a lower-energy route to m/z 59 than the formation of protonated allyl alcohol previously suggested by automated spectral prediction approaches. A semiquantitative energy transfer model was used to assess the compatibility of the calculated barriers with the experimentally accessible collision-energy range. Within the limitations of this qualitative treatment, the combined results constrain plausible first-order dissociation pathways and provide a mechanistic framework for future quantitative studies based on precursor internal-energy distributions and RRKM kinetics.

Publication date: Available online 10 October 2026 Source: TrAC Trends in Analytical Chemistry Author(s): Fengyang Jing, Mingchao Wang, Liliang Wen, Xinyu Liu, Guowang Xu

Publication date: Available online 9 October 2026 Source: Journal of Proteomics Author(s): Darío Méndez-Cuadro, Ali N. Kamali, Clara Ruiz, Susana Pérez-Benavente, María Luisa Hernáez, Erika Rodríguez-Cavallo, Antonio Puyet, José M. Bautista, Amalia Diez

Screening 20 amino acids on 18 polar stationary phases produces a dataset that can be re-queried for any analyte subset, returning the optimal column without new experiments. The approach yielded a validated assay for branched-chain amino acids requiring neither derivatization nor mass spectrometry. ABSTRACT A column ranking system was developed for the separation of all 20 proteinogenic amino acids using hydrophilic interaction liquid chromatography mode across 18 polar stationary phases with acetonitrile/aqueous mobile phases. Each amino acid was individually evaluated on all columns using gradient elution, and the retention time data were compiled into a statistical ranking algorithm that enables selection of any analyte subset and identifies the column providing the greatest separation between successively eluting analytes. Since most of these analytes lack strong chromophores, evaporative light scattering detection was employed for quantitative detection. Mobile phase pH (3.5 to 6.0) and ammonium formate concentration (10 to 100 mM) were then optimized on the three highest-ranked columns (Accucore-150-Amide HILIC, TSKgel Amide-80, and Poroshell 120 HILIC-OH5). Retention of most amino acids was insensitive to pH, whereas arginine and lysine showed inverse dependence on buffer concentration compared with all other analytes, and 50 mM ammonium formate without pH adjustment gave the best compromise for the complete analyte set. Re-querying the ranking algorithm for smaller analyte subsets returned a different optimal column in each case, confirming that no single stationary phase is universally preferable. Knowledge gained from evaluating the design space facilitated the rapid development of a quantitative method for the determination of the amino acid composition of a capsule formulation. The isocratic assay was linear for leucine, isoleucine, and valine over approximately 0.1 to 1.0 mg/mL (R 2 ≥ 0.997), recovered 102%–104% of label claim across six independent preparations, and gave injection precision of ≤ 0.45% relative standard deviation with quantitation limits of ≤ 114 µg/mL.

AbstractIsotope distribution prediction is an important part of mass spectrometry data analysis. A variety of strategies have been developed, including brute-force polynomial methods and Fourier-transform (FT) convolution methods. Here, we present a novel neural network (NN) approach to isotope prediction. These NN-based tools are distributed in a new package, IsoGen, alongside FT-based tools. We show that NNs perform as well as existing approaches when predicting isotope distributions for molecules with natural isotope ratios. We then demonstrate the capability of NNs for transfer learning, a method by which existing models that have been trained to perform one task can be reused as a starting point to train models for a second task. Here, an NN that has been trained to predict isotope distributions for molecules with natural isotope ratios can be retrained to predict distributions for molecules with perturbed isotope ratios. We also demonstrate that these training distributions do not need to be produced theoretically but can be extracted from experimental data in which the underlying isotopic composition is not known. Overall, NNs provide a robust method for isotope prediction that can be extended to applications in which the isotope distributions can be measured but not easily predefined.

AbstractSingle-cell mass spectrometry (MS) faces significant challenges in covering low-abundance and poorly ionizable metabolites, hindering comprehensive single-cell metabolomics studies of disease and life processes. Herein, we proposed a new single-cell MS method based on a pulled flowprobe that enables online static-zone metabolite enrichment and derivatization of cis-diol metabolites, thereby greatly enhancing metabolite coverage. A stationary sample band was observed within the continuously flowing liquid microjunction of the pulled flowprobe when the inner capillary was substantially retracted inside the outer capillary. A larger retraction distance and lower solvent flowrate were found to benefit band formation, and the band served as a static zone to enrich analytes, achieving up to 50-fold signal enhancement. Then, a benzylboronic acid derivatization reagent was introduced into this band, where both the reagent and cis-diol metabolites were enriched to achieve static derivatization, yielding faster reaction kinetics (< 1/4 the time to reach maximum yield) and greatly reduced band diffusion/dilution (peak width: 30 s vs > 100 s) compared with the traditional dynamic online derivatization. Then, the new single-cell MS method with online enrichment and static-zone derivatization was established and enhanced overall metabolite coverage more than two-fold (53 vs 24), and specifically three-fold for cis-diol metabolites from a single cell, compared to the traditional method using dynamic derivatization. Finally, the new single-cell MS method was applied to the neuronal injury study, and six metabolites involved in oxidative stress, myelin damage, and DNA damage pathways were found to be significantly altered between injured and normal cells. These results highlight the advances of our method in expanding the molecular understanding at the single-cell level to uncover disease mechanisms.

AbstractParallel accumulation with mobility-aligned fragmentation (PAMAF) achieves near-complete ion utilization and high spectral specificity by fragmenting all mobility-separated precursors without quadrupole isolation. Leveraging the ultrahigh mobility resolution of SLIM, this quadrupole-free strategy maximizes ion utilization efficiency and offers a promising approach in mass spectrometry-based proteomics, particularly for low-abundance peptides or low-input samples. However, the unique data structure of PAMAF, where precursor−fragment relationships are encoded along the mobility dimension, is not ideally suited to many existing peptide identification tools. Here, we present xTracer, an untargeted peptide identification algorithm developed specifically for PAMAF data. xTracer integrates correlations across both chromatographic and mobility dimensions to associate precursor and fragment ions, reconstruct pseudo-spectra, and enable database searching using well-established DDA search engines. Applied to datasets with varying sample loads and acquisition throughputs, xTracer consistently achieved robust and reproducible peptide identifications, outperforming both single-domain correlation strategies and diaTracer, which was developed for diaPASEF data. Overall, xTracer provides a versatile and high-efficiency computational framework for reconstructing pseudo-spectra from quadrupole-free, mobility-aligned fragmentation data, enhancing the analytical power of high-resolution ion mobility-based proteomics.

AbstractAn Au−TiO2 Janus material was designed to integrate exosome capture with dual post-translational modification (PTM) enrichment (palmitoylation and phosphorylation). The Au domain selectively enriched palmitoylated peptides through Au−S covalent interactions, while the TiO2 domain exhibited dual functions: enriching phosphorylated peptides through metal oxide affinity chromatography and capturing serum exosomes through specific interactions with phosphate groups on the exosomal lipid bilayers. Coupled with mass spectrometry, the Au−TiO2 Janus material exhibited excellent selectivity and sensitivity for palmitoylated and phosphorylated peptides. When this strategy was applied to serum samples from patients with non-small-cell lung cancer (NSCLC) and normal controls, four differentially expressed dual-PTM proteins (SERPINA1, CFH, AHSG, and IGLL1) were identified, all of which are associated with inflammation and immune abnormalities in the tumor microenvironment of NSCLC. The developed strategy represents an integrated workflow that enables simultaneous profiling of exosomal palmitoylation and phosphorylation, providing insights into biomarker discovery in NSCLC.

AbstractOxidative stress following spinal cord injury (SCI) triggers diverse metabolic alterations, including those in the acrolein (ACR)-associated pathway, which involves reactive carbonyl species (RCSs), polyamines, amino acids, fatty acids, and lipids. Therefore, comprehensive mapping of these metabolites is critical for understanding disease progression of SCI. Although matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI MSI) is widely used to map endogenous compounds, the simultaneous broad-spectrum detection of multiple analyte classes within the oxidative stress network remains challenging. Thus, we developed a cooperative matrix (co-matrix) composed of 2-hydrazinoquinoline (2-HQ) and α-cyano-4-hydroxycinnamic acid (CHCA) for the MALDI MSI of rat spinal cord tissue after SCI. In this system, ion-pair formed between 2-HQ and CHCA achieved crystallization uniformity and spot-to-spot reproducibility, while 2-HQ selectively derivatizes RCSs in situ. Density functional theory calculations further revealed that the ionicity of the co-matrix enhances analyte ionization. Using this co-matrix, we imaged 41 distinct metabolites in rat SCI tissue sections with high signal-to-noise ratios, including two carbonyl compounds associated with ACR-related oxidative stress pathways. In comparison, CHCA alone allowed imaging of only 15 metabolites (predominantly lipids), while 2-HQ alone detected one. Temporal heatmap analysis of nine metabolites within the ACR-associated pathway revealed coordinated dynamics between ACR and glutathione, both rebounding at day 7 (one-way ANOVA, p < 0.01). Overall, this study provides an efficient strategy for the comprehensive imaging analysis of multiple metabolite classes in complex injured biological systems.

Publication date: Available online 8 October 2026 Source: Analytica Chimica Acta Author(s): Zuowei Huang, Yao Pan, Naisheng Wu, Fangling Wu, Chuan-Fan Ding

Publication date: Available online 8 October 2026 Source: Journal of Chromatography A Author(s): Fuyan Liu, Haolin Zhang, Ying Qu, Haojie Zheng, Shengxian Liu, Xiao-feng Zhang

AbstractOver 30 years ago, the Modular ICR Data Acquisition System (MIDAS) was assembled, developed, and deployed on the then-new Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR MS) instruments at the National High Magnetic Field Laboratory. The system was based on National Instruments electronics and software, with interface electronics and control code built and written in-house. Capable of controlling all aspects of FT-ICR MS data acquisition and data processing, the system formed the basis of MagLab instrument control for the following three decades. Here, we report on recent progress in data acquisition and analysis capabilities, motivated by the coupling of an Orbitrap Eclipse Tribrid mass spectrometer to the 14.5 and 21 T FT-ICR instruments. The new system is based on more recent National Instruments PXIe control boards, and leverages and extends the vendor instrument control hardware and software for a seamless integration of the FT-ICR MS instrumentation with the Eclipse front-end. The entire instrument is controlled from Tribrid Series Tune, Method Editor, and Xcalibur software. All mass analyzers, including the ICR analyzer, can be operated in parallel, exploiting the existing Tribrid architecture, and resulting in duty cycle improvements over previous implementations.

AbstractFunctional annotation of microbial genes lags behind the pace of genome sequencing, leaving major gaps in our understanding of microbial metabolism. Combining genetic perturbation with untargeted stable isotope tracing metabolomics provides a powerful strategy for identifying pathway intermediates and elucidating microbial metabolic pathways. To streamline this workflow, we developed IsoPairFinder, a computational tool that prioritizes pathway-intermediate feature pairs by analyzing paired unlabeled (12C) and 13C-labeled metabolomics datasets from genetically perturbed microbes. By consolidating redundant liquid chromatography–mass spectrometry (LC–MS) features and pairing features across unlabeled and labeled samples, IsoPairFinder reduces candidate lists to plausible isotope-paired intermediates for downstream validation. We demonstrate the utility of IsoPairFinder in a case study of uric acid catabolism in Clostridium sporogenes, where it filters redundant features and prioritizes LC–MS feature pairs representing gene-associated pathway intermediates. IsoPairFinder is available as an open-source R package and as a web-based workflow within GNPS2. By integrating differential analysis and isotope-pair detection into a single workflow, IsoPairFinder enables microbiologists to connect metabolomic features with microbial gene function more efficiently, thereby accelerating microbial pathway discovery.

AbstractProton transfer reaction mass spectrometry (PTR-MS) is widely used for the real-time detection of volatile organic compounds (VOCs). Previous efforts to improve PTR-MS sensitivity have mainly focused on electric-field optimization, whereas the influence of macroscopic gas flow on ion transport has received much less attention, despite the inevitable gas flow induced by pressure gradients within the drift tube. In this study, a coupled CFD–ion trajectory simulation approach was employed to systematically investigate the influence of gas flow on ion transport and the underlying mechanisms. The results show that, under the combined effects of the electric field and gas flow, ion transport is mainly influenced by three mechanisms: collision focusing, aerodynamic focusing, and recirculation loss. At low to intermediate pressures, collision focusing and aerodynamic focusing jointly enhance ion transport, resulting in an increase in ion transmission efficiency with increasing pressure. For m/z 100, the transmission efficiency increased from 33% at 100 Pa to 65% at 1000 Pa. At higher pressures, the recirculation region gradually developed and extended toward the main ion transport pathway. The resulting recirculation loss increasingly competed with aerodynamic focusing, leading to a gradual decrease in ion transmission efficiency; for m/z 100, the transmission efficiency decreased to 4% at 8000 Pa. A symmetric inlet sampling structure was further proposed to regulate the flow field. At 6000 Pa, this design substantially reduced the recirculation region and increased the ion transmission efficiency of m/z 100 from 30% to 75%, further supporting the proposed interpretation of recirculation-induced ion loss. These results reveal how gas flow modulates ion transport in PTR-MS drift tubes and provide a physical basis for selecting operating conditions, optimizing flow fields, and improving drift-tube design.

Prostate cancer (PC) bone metastases (PCBM) are a debilitating disease morbidity that primarily affects the axial skeleton. PCBM are predominantly osteosclerotic with mixed osteosclerotic/osteolytic features, including irregular bone deposition, loss of collagen alignment and increased porosity that mimic features of woven bone formed during development and repair. We hypothesize that progression of PCBM is driven by interactions between tumor cells and the bone microenvironment and is associated with changes in the stromal compartment. We performed tandem mass tag mass spectrometry proteomics on lumbar vertebral specimens from 32 cadaveric PCBM specimens and 3 age-matched controls. Unsupervised clustering segregated specimens into three clusters associated with benign, mixed, and osteosclerotic lesion states, characterized by distinct immune-, tumor-, and osteogenic-associated protein signatures. Histological analysis showed tumor infiltration was accompanied by marrow fibrosis and increased collagen III deposition. We identified a marker signature associated with osteosclerotic remodeling and mapped this signature to independent metastatic PC transcriptomic datasets. The proteomics-derived markers reproduced similar molecular groupings at RNA level, and robustly segregated bone PCBMs from soft tissue metastases PC in RNA data. Together, these findings define molecularly distinct states of tumor-driven changes in PCBM that extend beyond histological classification and may inform biomarker development and therapeutic stratification.

Ogerin, a positive regulator of GPR68, reduces infarct volume and attenuates blood-brain barrier (BBB) leakage post transient middle cerebral artery occlusion (tMCAO). These data support the potential use of Ogerin for ischemic protection. For therapeutic interventions, tissue distribution, kinetics, and brain penetration are important characteristics for a compound. For these reasons, we performed liquid chromatography-mass spectrometry (LC-MS) analysis of Ogerin in mice. At 3 hours following intraperitoneal (IP) injection, liver exhibited highest level of Ogerin among all major organs assessed. We further analyzed time-dependent changes in Ogerin concentration in serum following intravenous delivery. Brain Ogerin level was ~140 ng/g at 2 hour and ~0.06ng/g at 24 hours. The brain-to-serum ratio of Ogerin was ~0.6 at 5 hr. To determine the effect of Ogerin on signaling, we collected samples 24 hours after tMCAO with or without Ogerin delivered and performed Western blotting. Consistent with the diminished level of Ogerin in brain at 24 hour, tMCAO increased similar changes in phosphorylation of PKA substrates and PKC substrates in vehicle- and Ogerin-treated groups. The pharmacokinetic data suggests that Ogerin is effective mainly during acute hours after injection. This finding generates important insights on the design of effective protocol for Ogerin delivery to potentiate GPR68 function in vivo.

Pannexin 1 (PANX1) is a channel-forming glycoprotein that has been implicated in regulating melanoma cell properties such as growth, migration, and invasion. Here we report that the CRISPR-Cas9 mediated ablation of PANX1 or channel inhibition with probenecid shifted A375-P cell cycle distribution towards G2/M, while channel inhibition with spironolactone stalled cell cycle progression at the G1/S checkpoint regardless of PANX1 expression. Bulk RNA sequencing revealed cell cycle related gene expression was downregulated with PANX1 targeting strategies and this was exacerbated when PANX1 deficient cells were treated with spironolactone. When grown as spheroids, we found the deletion and inhibition of PANX1 disrupted spheroid compaction, with spheroids displaying poorly defined borders and reduced circularity. The deletion of PANX1 increased spheroid fragmentation, and this phenotype was intensified when spheroids devoid of PANX1 were treated with spironolactone, highlighting a potential synthetic lethal effect. Using liquid chromatography mass spectrometry, we sought to determine whether PANX1 had binding partners that may act to stabilize spheroid integrity and found that PANX1 co-immunoprecipitated various cell adhesion molecules such as {beta}-actin and F-actin-capping protein subunit -1, suggesting PANX1 and its interacting partners may stabilize cell-cell contacts. When control and PANX1 ablated cells were grown in chick chorioallantoic membrane xenografts to assess their tumour growth characteristics, we discovered that the deletion of PANX1 reduced tumour surface area and viability. Our findings indicate that PANX1 regulates cell cycle progression and the structural architecture of A375-P melanoma tumours, highlighting the therapeutic utility of targeting PANX1 in melanoma.

Accurate identification of intact proteoforms and their complexes directly from heterogenous biological samples is essential to understand their role in health and disease. While native top-down mass spectrometry (nTDMS) workflows enable this, the extreme molecular complexity of biological samples inadvertently results in overlapping signals which confounds protein identification. One approach to resolving this complexity is gas-phase ion-ion reactions which separate analytical targets according to their original charge state. Charge reduction techniques coupled to mass spectrometry resolve signal overlap in m/z space, when ions differ in charge, and so they are especially useful in the analysis of large biomolecules like proteins that form multiple charge states during electrospray ionisation. Previously, we investigated multistage nTDMS of intact proteins sampled directly from tissue sections where the first experiment stage was separation by charge reduction, followed by collisional activation for sequence ion production. The specificity of product ion spectra was improved but at the expense of signal intensity owing to inefficient use of charge-reduced product ions. Here we establish the use of synchronous precursor selection (SPS) for nTDMS via multinotch isolation in a linear ion trap, enabling simultaneous isolation of multiple targets in m/z space and thereby increasing the number of ions available for fragmentation. We implemented SPS for nTDMS across three charge reduction techniques and collision, electron and photon mediated fragmentation methods on commercial and modified mass spectrometers. Improvements to the signal-to-noise ratio of product ions resulted in greater sequence coverage for example intact proteins and complexes up to ~44 kDa using the SPS workflow. We provide a freely-available SPS target calculator, Novalap, that enables simple SPS method development. SPS nTDMS is a methodological breakthrough for proteoform identification in complex mixtures, where specificity is essential, sequence coverage is desired and ion abundance is at a premium.

(1. Guangdong Huisheng Testing Technology Co., Ltd.) Abstract: Soft ionization mass spectrometry is widely applied in fields such as pharmaceuticals, cosmetics, environmental monitoring, and food safety; however, its fundamental principles remain subject to considerable debate, rendering it a "black-box" technology. This review summarizes the basic principles of electrospray ionization (ESI), matrix-assisted laser desorption (MALDI), and desorption electrospray ionization (DESI), and establishes "one theory, two equations, and three instruments" as the theoretical and practical foundation for soft ionization mass spectrometry. Furthermore, this study discusses the electromagnetic applications of soft ionization mass spectrometry, thereby expanding its scope of research and application.

Formalin-fixed paraffin-embedded (FFPE) samples are central for clinical research and spatial proteomics. Here, the authors present a streamlined micro-FFPE proteomics workflow that enables rapid, high-throughput spatial proteomics of laser-capture microdissected tissue.

Photosynthetic electron transport is tightly regulated to balance ATP and NADPH production and prevent over-reduction of the photosynthetic machinery. How this balance is maintained under severe ATP limitation, particularly under anoxia, is not fully resolved. Here, we used several deletion mutants of chloroplast ATP synthase subunits from Chlamydomonas reinhardtii to examine how electron flow is reorganized under anoxic conditions through the interplay between linear electron flow, cyclic electron flow, and alternative electron sinks. Using a combination of optical spectroscopy methods and membrane inlet mass spectrometry, we characterized changes in photosynthetic electron transport, proton motive force relaxation and gas exchange. Under oxic conditions, the {Delta}atpH mutant (lacking the c-subunit) showed strong acceptor-side limitation at photosystem I (PSI), whereas atpC1-2 (lacking the {gamma}-subunit) resembled the wild type. Under anoxia, this limitation was partially relieved, coinciding with sustained electron transport and prolonged hydrogen production. In particular, the {Delta}atpH mutant exhibited increased cyclic electron flow under oxic conditions and maintained PSI activity under anoxia despite impaired ATP synthesis. Prolonged hydrogen production was also observed in atpC1-2, which did not share the increased respiration of {Delta}atpH. Hydrogenase activity under anoxia is consistent with a role as an electron sink that may help alleviate PSI acceptor-side limitation and rebalance the redox state of the electron transport chain. These findings show that ATP synthase deficiency reorganizes photosynthetic electron flow and promotes prolonged hydrogen production, and point to hydrogenase as a candidate electron sink under energy-constrained conditions.

Journal of Mass Spectrometry, Volume 61, Issue 10, October 2026.

A green PDMS sorptive sampling loop coupled with complementary liquid and gas chromatography–mass spectrometry enabled detection of migrating chemicals from plastic food contact materials under everyday-use scenarios. The approach revealed diverse additives and non-intentionally added substances, supporting improved exposure assessment of plastic-derived migrants. ABSTRACT Comprehensive analysis of migrating compounds from plastic food contact materials (FCMs) is analytically demanding due to the structural diversity and broad physicochemical properties of intentionally and non-intentionally added substances (IAS and NIAS). This necessitates the development of advanced, multidimensional separation techniques coupled with high-resolution detection for trace-level characterization. Five million tones of chemical additives are incorporated into plastic FCMs annually, which is concerning considering the health risks associated with human exposure to migrating chemicals. This study provides a simplified green sorptive sampling loop for detecting and quantifying IAS and NIAS that migrate from FCMs during everyday use. A polydimethylsiloxane (PDMS) sorptive sampler loop was used as the sampling device, allowing migrated compounds to be enriched directly from the sample matrix. After extraction, the same sampler format was compatible with two analytical workflows: thermal desorption directly into the GC inlet for GC×GC–TOFMS analysis, or liquid back-extraction into solvent for subsequent UHPLC-IMS-MS analysis. Complementary chromatography and ion mobility high-resolution mass spectrometry (UHPLC–IMS–MS and GC×GC–TOFMS) enabled the detection and quantification of a range of chemical compounds at trace levels, including phthalates, UV absorbers, stabilizers, surfactants, and hydrocarbons. Over 30 compounds were detected as migrating from FCMs using GC–MS, and 26 compounds were identified using LC–MS. Unknown target identification using LC–MS was aided by the use of collision cross section (CCS) values, thus strengthening putative identification. Limits of detection of the eight target analytes ranged from 0.023 to 97 ng L−1 for LC–MS and IAS were detected at concentrations ranging from 0.0065 to ∼25 µg L− 1. Our study exemplifies the wide range of chemical compounds that migrate from FCMs during everyday FCM use. The green sampling technique presented here allowed the quantification of daily exposure to these chemicals and has potential application to human health and environmental risk assessments.

ABSTRACT In this work, a covalent organic framework (COF)-based nanofibrous composite (PAN@TFPB-TAPB) was fabricated through an in situ growth strategy and explored as a high-performance sorbent for thin film microextraction (TFME). Benefiting from the integration of electrospun polyacrylonitrile (PAN) nanofibers and TFPB-TAPB (2,4,6-trihydroxybenzene-1,3,5-tricarbaldehyde [TFPB] and 1,3,5-tris(4-aminophenylbenzene) [TAPB]), the composite mitigated the aggregation of conventional COF powders and provided accessible adsorption sites with good structural stability. The as-prepared PAN@TFPB-TAPB sorbent exhibited higher extraction efficiency toward seven organophosphate esters (OPEs) compared with pure PAN and TFPB-TAPB. On this basis, a sensitive and reliable TFME-gas chromatography-mass spectrometry method was established for the simultaneous enrichment and determination of OPEs in degradable plastic samples. Under the optimal conditions, the proposed method displayed wide linear ranges, low limits of detection, good precision, and satisfactory recoveries. Furthermore, this method was successfully applied to the analysis of OPEs in real complex plastic samples, demonstrating its great practical potential for the efficient monitoring of OPEs in environmental and commodity-related matrices.

In this work. Vadas et al. report how Roginolisib, a phosphoinositide 3-kinase delta specific inhibitor, locks the enzyme in an inactive conformation, providing high potency and specificity. This binding mode results in reduced phosphatidylinositol 3,4,5-trisphosphate formation in tumour samples of CLL patients receiving Roginolisib.

AbstractPlasma proteomics has emerged as a powerful approach for interrogating human biology, identifying disease-associated proteomic changes, and advancing precision diagnostics. In recent years, affinity-based plasma proteomics platforms with predefined protein panels, such as Olink and SomaScan, have emerged to complement bottom-up mass spectrometry (BUP). This study leverages a novel mass spectrometry platform to capture targeted proteoform information lost by mainline antibody-, aptamer-, and BUP-driven workflows. The Plasma Proteoform Assay (PPA) uses Individual Ion Mass Spectrometry (I2MS) to resolve mixtures of intact proteins presented by direct injection. Two proteoform panels, PPA 526 and PPA 1514, were defined from human plasma samples obtained from 81 individuals. The panels quantify 526 proteoforms derived from 59 genes and 1,514 proteoforms from 155 genes, respectively. Across both panels, the proportion of targeted proteoforms with CVs below 20% ranged from 59% to 80%. PPA was benchmarked in studies including 9 pooled plasma samples derived from subjects with hepatic cirrhosis (N = 30 individuals) and a cohort of resilient agers carrying a SERPINE1 (PAI-1) mutation (N = 27 individuals). PPA signatures distinguished SERPINE1 mutation carriers from affected individuals and provided sufficient resolution to discriminate among cirrhosis disease stages. In summary, we present PPA 526 and PPA 1514, the first scalable plasma proteoform panels capable of tracking hundreds to thousands of targets in a few minutes per sample.

AbstractMass spectrometry imaging (MSI) enables in situ visualization of small-molecule distributions in plants. However, MSI data interpretation often relies on extensive prior chemical knowledge, limiting the rapid screening of specific compound classes. Furthermore, structural analysis via LC/MS typically depends on tandem mass spectrometry, which is not routinely integrated into standard MSI workflows. To address this, we established a desorption electrospray ionization (DESI)-enabled, signature-ion-guided natural product imaging (DESIGNi) method. By acquiring high-resolution fragment ion data using a multi-reflecting time-of-flight (MRT) mass spectrometer, this approach enables rapid visualization of compounds containing specific building blocks based on their diagnostic fragment ions. As a proof of concept, we focused on aromatic acylated derivatives. The method was developed and optimized using the phenylethanoid glycosides in Forsythia fruit, and the accuracy of the resulting distributions was validated by LC/MS. We applied this approach to seven additional medicinal or edible plants and mapped the distribution of phenylethanoid glycosides, phenolic acid oligomers, benzyl ester glycosides, amides, and diarylheptanoids. By tracing signature ions to their corresponding full-scan spectra, MSI enabled the discovery and preliminary identification of rare or potential novel compounds. This study presents a new strategy for rapid visual screening of plant natural products using MSI.

AbstractMatrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) is widely used for polymer characterization. However, the compositional analysis of copolymers becomes increasingly challenging at higher molecular weights because multiple polymer compositions and their isotopic distributions yield overlapping peaks. Here, we present a predictive framework that facilitates the interpretation of complex copolymer mass spectra by revealing how individual copolymer species contribute to the observed mass spectral features and by identifying the possible compositions associated with each spectral peak. The framework further determines the upper measurable mass limit (UMML), defined as the molecular-weight limit below which neighboring peaks remain distinguishable under specified instrumental conditions. Starting from a specified main polymer composition, the algorithm identifies neighboring and overlapping feasible compositions within the corresponding local m/z region for both copolymers and terpolymers. Their relative contributions are estimated using a statistical description of monomer incorporation, while their isotope distributions are calculated using m/z-dependent peak profiles determined experimentally. The results demonstrate that the UMML is governed by the system-specific mathematical structure and density of feasible compositions, isotope distributions, and instrumental resolving power. Although the numerical UMML values are instrument- and criterion-specific, the framework is transferable to other mass spectrometric platforms by introducing the corresponding resolving-power or peak-width vs. m/z function. The method, therefore, provides both a detailed map of the local composition landscape and a priori estimate of the molecular-weight range over which meaningful compositional information can be obtained.

AbstractSolid-phase microextraction (SPME) with biocompatible coating material is highly compatible with ambient mass spectrometry (AMS), such as direct analysis in real time (DART), for improving sensitivity and reducing matrix effects. However, the practical throughput of SPME−DART-MS remains limited by the mismatch between parallel sample preparation and device-to-source transfer. Here, we introduce a 96-sample parallel BioSPME-DART-MS platform that integrates automated SPME extraction, 96-channel liquid transfer, and a matched 96-position DART mesh interface. This design enables 96 biological samples to be processed in a plate-based format, greatly improves workflow transferability. Thin HLB/PAN-coated SPME blades were used to provide bio-compatible extraction and cleanup from whole blood, plasma, and urine. After desorption in 200 μL of solvent, only 5 μL of the extract was transferred to the DART mesh for rapid MS/MS screening, while the remaining solution was retained for sequential LC−MS/MS confirmation without additional sample preparation. The system enabling an average analysis time of approximately 40 s per sample. Using six fentanyl and its analogues as model analytes, the BioSPME-DART-MS method achieved good sensitivity across the three biofluids, with limits of detection of 0.10−0.50 ng mL−1 in whole blood, 0.03−0.20 ng mL−1 in plasma, and 0.01−0.20 ng mL−1 in urine. In addition, a comparative study of absolute matrix effects revealed that chromatography-free DART-MS and blade spray-MS remained susceptible to ion suppression, whereas LC−ESI-MS showed negligible matrix effects. This platform establishes a high-throughput, two-tier SPME−MS workflow that combines rapid ambient MS screening with chromatography-based confirmation.

AbstractElectrostatic repulsion hydrophilic interaction liquid chromatography (ERLIC) provides unique selectivity for highly polar and charged analytes, yet method development remains challenging. Careful optimization of organic solvent gradients and buffer concentrations is essential to achieve optimal selectivity. However, application of a pH gradient in addition to organic solvent and buffer concentration gradients can enable mixed-mode interactions beyond those governed solely by electrostatic repulsion. In this work, we introduce Electrostatic Attraction/Repulsion Hydrophilic Interaction Liquid Chromatography (EARLIC), a novel separation mode that extends the selectivity of ERLIC by leveraging both electrostatic attraction and repulsion through pH gradient modulation of analyte−stationary phase interactions. Fundamental retention mechanism differences between these separation modes are proposed while also outlining key chromatography practices for enhanced selectivity. In addition, an ERLIC/EARLIC screening platform integrating cation and anion exchange columns with twelve mobile phases to systematically modulate electrostatic and hydrophilic interactions is introduced. Automated column and mobile phase switching valves enabled rapid scouting and efficient assay development while also minimizing manual intervention. This workflow demonstrated broad applicability across nucleotides, N-glycans, synthetic precursors, intact glycoproteins, and aminoglycoside antibiotics. Compared to classical HILIC, EARLIC improved retention of highly hydrophilic species, delivered sharper peaks in high-salt matrices, and provided orthogonal selectivity for charged moieties. Coupling ERLIC/EARLIC to mass spectrometry streamlined sensitive quantitation of kanamycin in cell culture matrices, confirming compatibility with complex sample loads. This analytical framework establishes a systematic approach for selecting the optimal combination of stationary phase charge, buffer system, ionic strength, pH, and organic fraction, accelerating ERLIC/EARLIC adoption across both academic and industrial sectors.

AbstractAccessory-mineral U−Pb geochronology by laser ablation quadrupole inductively coupled plasma mass spectrometry (LA-Q-ICP-MS) provides valuable temporal constraints on Earth and planetary processes. However, its application at sub-20 μm spatial resolution is hindered by matrix-dependent Pb/U downhole fractionation, which compromises the accuracy of non-matrix-matched calibration. Here, xenotime BS-1, allanite AMK, and titanite MKED1 were analyzed at spot sizes of 16 and 10 μm using Tanz zircon as the external calibration reference material. Under dry-ablation, the conventional mean-of-ratios approach produced relative 206Pb/238U ratio biases of 14.2−21.8%, reflecting pronounced matrix-dependent differences in downhole Pb/U fractionation between zircon calibrant and the other accessory minerals. To overcome this limitation, we developed a quadratic polynomial regression intercept method that extrapolates the time-resolved Pb/U fractionation profile to the onset of ablation. The absolute bias reduced to 2.19−11.1% using the quadratic polynomial regression correction under dry ablation conditions. When combined with pre-cell water-vapor-assisted laser ablation, the method enables accurate non-matrix-matched U−Pb dating of xenotime, allanite, and titanite using spot sizes as small as 10 μm, with bias of only 0.05−0.74%. These results establish a practical strategy for routine sub-20 μm multimineral U−Pb geochronology by LA-Q-ICP-MS.

AbstractLaser desorption/ionization mass spectrometry offers distinct advantages for biomolecular analysis owing to its high salt tolerance, low sample consumption, and soft ionization capability. However, localized laser−sample interactions are inherently affected by heterogeneous distributions of analytes and materials, leading to substantial variation between measurements. Improving signal precision has therefore long been a central pursuit in mass spectrometric analysis for reliable qualitative and quantitative biomolecular information. Herein, we report a laser-induced graphene (LIG) microarray platform for enhancing analytical precision in surface-assisted laser desorption/ionization mass spectrometry (SALDI-MS). A straightforward thermal confinement strategy enabled high-resolution LIG patterning under CO2 laser irradiation. Using an unmodified commercial laser cutter, monolithic porous LIG domains with feature sizes as small as 60 μm, below the MS laser spot diameter, were directly patterned on polyimide films. The wettability contrast between hydrophilic LIG and hydrophobic polyimide guided analyte accumulation onto SALDI-active LIG spots, which were fully interrogated by the MS laser for reproducible desorption/ionization. This integrated control over LIG feature size and analyte localization reduced the relative standard deviation of MS signal intensity from 78.47% on the unconfined substrate to 6.27% across 30 microarray spots. The platform demonstrated applicability to diverse biomolecules in both positive and negative ion modes. Quantitative accuracy was further demonstrated through enzyme kinetic studies, giving kinetic parameters consistent with conventional colorimetric results. More importantly, LIG microarray-assisted SALDI-MS enables direct molecular tracking of colorless native substrate turnover, underscoring the broader potential of nanostructured carbon interfaces for reaction-resolved mass spectrometric analysis.

AbstractIon mobility mass spectrometry (IM-MS) provides valuable structural information about protein shape and size through collision cross section (CCS). However, it lacks atomic level structural detail. While AlphaFold has been successful in predicting monomeric protein structure, it can struggle with modeling protein complexes. To address these limitations, we developed a method that integrates IM-MS data with AlphaFold and Rosetta to improve complex structure prediction. Our approach docks AlphaFold predicted subunits with Rosetta and selects the resulting models with a newly developed score that incorporates experimental or simulated CCS data. Using this strategy, we were able to improve normalized root mean square deviation (RMSD100) values for 26 of 38 (68%) complexes compared to AlphaFold-Multimer. Furthermore, 14 of these systems improved significantly from greater than 4 Å RMSD100 to less than 4 Å. This method demonstrates a robust approach to overcome limitations in complex assembly modeling.

Reliable quality control (QC) is essential for reproducible biological mass spectrometry, yet QC information is still typically stored in tool-specific, poorly interoperable formats that hinder comparison, reuse, and transparent reporting. We present mzQC, a community-developed standard from the HUPO Proteomics Standards Initiative for the compact, machine-readable representation of QC metrics and their associated metadata across mass spectrometry workflows. mzQC is implemented in JSON, organized to support both individual mass spectrometry acquisitions and collections thereof, with formal QC metrics definitions supported by controlled vocabularies to ensure unambiguous metric interpretation and semantic consistency. The format is supported by validation tools and reference libraries in Python, R, and Java, facilitating integration into existing software ecosystems. We demonstrate the utility of mzQC across diverse analytical modalities and QC settings, spanning longitudinal instrument monitoring, acquisition-method evaluation, study-level quality assessment, repository-scale data characterization, and spatially resolved mass spectrometry imaging. Together, these use cases show that mzQC provides not merely a file format, but a shared foundation for interoperable QC reporting, large-scale data assessment, and more rigorous, reproducible, and reusable mass spectrometry-based research.

AbstractWe have measured the rate coefficient for the reaction between the 2-methylpropan-1-yl radical and molecular oxygen as a function of temperature and pressure in both He and N2 bath gases using photoionization mass spectrometry. Similar measurements were performed for the 2-methylpropan-2-yl radical. It was found that 2-methylpropan-1-yl reacts much slower with O2 than 2-methylpropan-2-yl both in the falloff region and near the high-pressure limit. We complemented the experimental work by constructing master-equation models for both reaction systems to simulate their kinetics under conditions not covered by experiments. By optimizing the value of few key parameters against measured data, the models were able to reproduce the observed temperature and pressure dependencies of both rate coefficients. To facilitate the use of present results in modeling, PLOG and Chebyshev rate-coefficient parametrizations are provided. Although 2-methylpropan-1-yl reacts much slower with O2 than 2-methylpropan-2-yl, the former reaction generates more products that lead to chain-propagation and -branching than the latter, which almost exclusively forms 2-methylpropene and hydroperoxyl and is thus chain-terminating.

AbstractLipid–protein interactions play critical roles in cellular function, yet their site-resolved characterization remains challenging due to the dynamic nature of lipid binding and the limited availability of chemoselective strategies for covalently capturing native lipid–protein contacts. Here, we introduce aziridination-based lipid–protein crosslinking coupled with mass spectrometry (Azi-LPXL-MS), a chemoselective strategy that installs an N–H aziridine moiety onto acyl chains of native unsaturated lipids and enables subsequent crosslinking to proximal lysine residues using the amine-reactive reagent disuccinimidyl suberate (DSS). This integrated workflow simultaneously identifies lipid-binding sites and intraprotein peptide–peptide distance constraints, providing direct insight into lipid binding and binding-induced conformational changes within a single experiment. Application of Azi-LPXL-MS to β-lactoglobulin (BLG) demonstrates these capabilities, consistent with known structural models, while additionally providing solution-phase and conformational information not accessible from static structures alone. The power of the method is further demonstrated in the integral membrane enzyme diacylglycerol acyltransferase 1 (DGAT1). Azi-LPXL-MS reveals phosphatidic acid (PA)-binding sites and maps lipid-dependent conformational rearrangements across both resolved and previously uncharacterized regions. These data further define an allosteric conformational network linking lipid engagement to distal structural changes. Integrated with site-directed mutagenesis and molecular docking, two potential PA-binding sites in DGAT1, located in a surface pocket and an internal chamber, were identified and functionally validated, further supporting the experimental findings. These results establish Azi-LPXL-MS as a site-resolved method for studying lipid–protein interactions, providing insight into how individual lipid species engage proteins and influence their conformations in biological systems.

AbstractFatty acids (FAs), as key lipids in energy storage and signaling, are dynamically regulated to maintain cellular homeostasis. FA profiling has become a valuable approach for investigating lipid reprogramming in disease. Although isomer-resolved mass spectrometry (MS) methods facilitate differentiation of FA isomers, quantitation is limited by the scarcity of isomer standards. Here, leveraging isobaric intramolecular Paternò–Büchi (i2PB) reactions, we develop an isomer-resolved multiplexed quantitation method for FA profiling. The i2PB reagents, synthesized via amidation of benzoyl-phenylalanine with the 6-plex TMT tags at near-quantitative conversion, overcome the low-yield limitations of conventional PB reactions for low-abundance lipids. Rapid i2PB reactions (4 s) enable online integration with liquid chromatography, while subsequent MS2 and MS3 analyses generate reporter ions for 6-channel FA quantitation at the sum composition and C═C location levels, respectively. For FA quantitation, this approach offers improved throughput, amol sensitivity, and a linear dynamic range of 2 orders of magnitude. Using i2PB, we achieve parallel quantitation of over 100 FAs with defined C═C locations in normal and breast cancer cells, providing new insights into metabolic reprogramming of FAs in breast cancer cells.

AbstractRNA N6-methyladenosine (m6A) deposition by the METTL3–METTL14 complex regulates RNA metabolism and thereby influences cell differentiation and stress responses. Dysregulated m6A deposition has been implicated in multiple cancers, where METTL3–METTL14 supports oncogenic programs. Yet the molecular basis of RNA recognition by this complex remains unclear, in part due to the lack of an RNA-bound structure of the full assembly. Here, we combined native mass spectrometry (MS), molecular modeling, biochemical assays, and cell-based studies to define how METTL3–METTL14 engages RNA and how this process can be perturbed through interface targeting. Native MS of the intact heterodimer revealed simultaneous binding of multiple RNA molecules, with RNA-dependent stoichiometries and higher-occupancy states consistent with cooperative interactions. Molecular dynamics simulations identified a structured RNA-bound assembly in which the METTL14 C-terminal RGG-rich region stabilizes two RNA molecules, supporting a pre-engaged substrate configuration. We further developed a focused library of METTL14-derived peptides that bind METTL3 and interfere with protein–protein interactions, identifying the minimal METTL14 epitope for interface engagement. The most potent peptide, R8–14, binds with submicromolar affinity, disrupts both METTL3–METTL14 association and higher-order RNA-bound states, and reduces m6A levels, c-Myc expression, and cancer cell viability. Together, these findings demonstrate that RNA recognition by METTL3–METTL14 is governed by multivalent, higher-order interactions that enhance binding avidity. Notably, this assembly can be perturbed allosterically through protein–protein interface targeting rather than active-site inhibition, highlighting multivalent RNA recognition as a mechanistically and pharmacologically actionable feature of the RNA m6A writer complex.

AbstractA mechanistic investigation of the gas-phase Cornforth rearrangement of protonated 2,4,5-trisubstituted oxazoles is presented. Upon collisional activation, these oxazoles undergo a pericyclic ring-opening to generate a nitrile ylide intermediate, which subsequently undergoes a 1,5-dipolar electrocyclization to yield the isomeric thiazole product. An oxygen-to-sulfur replacement was strategically employed as an isosteric labeling approach to probe and monitor the rearranged product ions, [PhCS]+ and [PhC2S]+, in the MS2 spectrum. Quantum chemical calculations at the M06-2X/def2-TZVP level revealed a strong preference for the Cornforth pathway and demonstrated the influence of para-substituents on the phenyl ring, correlating with the intensities of the rearranged product ions. Unlike the condensed-phase reaction, mass spectrometry revealed the potential reversibility of the gas-phase Cornforth rearrangement for trisubstituted oxazoles.

AbstractSex-wellness products, including herbal formulations, API-containing tablets, creams, and sprays, are widely used to enhance sexual performance, treat erectile dysfunction, or improve perceived sexual well-being. These products span a broad and heterogeneous market, ranging from regulated prescription pharmaceuticals to over-the-counter (OTC) preparations and illicit or counterfeit (with APIs) products distributed through informal channels and online platforms. Particularly, the circulation of counterfeit, adulterated, or products marketed as alternatives to phosphodiesterase type 5 inhibitors (PDE5i), represents a growing public health challenge, where PDE5i and certain antidepressants and anesthetics used for the treatment of premature ejaculation are often detected in unregulated formulations. Current analytical approaches for illegal substances in these formulations rely predominantly on laboratory-based techniques, such as LC-HRMS/MS, which require time-consuming sample preparation, skilled personnel, and centralized facilities. Faster and cheaper screening approaches, such as immunoassays (e.g., ELISA) and other rapid test kits, widely used due to their simplicity and low cost, are inherently target-specific and may suffer from cross-reactivity or limited selectivity. Portable mass spectrometry (PMS) instrumentation represents an effective alternative, enabling rapid, on-site screening of complex samples with enhanced selectivity and broader detection capabilities. In this work, a miniature ion trap system, equipped with atmospheric pressure chemical ionization (APCI) and thermal desorption (TD), enabling MS and MS/MS analyses with minimal sample preparation, was evaluated for the rapid screening of pharmaceutical compounds in sex-wellness products, including counterfeit and adulterated formulations. Besides qualitative identification, a semiquantitative analysis was also developed to estimate drug concentration. A complementary LC-HRMS/MS analysis provided confirmation and structural elucidation of the compounds detected during on-site screening. The PMS instrumentation provided rapid and reliable screening and semiquantitative capabilities with results consistent with those obtained by LC-HRMS/MS systems.

AbstractNeonicotinoids and organophosphates are important analytes due to their use as insecticides and environmental profiles. Cationized imidacloprid and chlorpyrifos as prototypical examples of these were analyzed with drift tube, traveling wave, trapped ion, and cyclic ion mobility mass spectrometry, with experimental collision cross sections (ExpCCSN2) derived for each to help understand their gas phase structures. The ExpCCSN2 of potassiated imidacloprid and potassiated chlorpyrifos are reported for the first time. The cross-platform ExpCCSN2 for [imidacloprid + K]+ is 160–165 Å2 and for [chlorpyrifos + K]+ is 175–176 Å2. Consistent assignment of the [imidacloprid + H]+ structure is achieved based on combining evidence from current work, literature interlaboratory CCS values, DFT energetics, predicted CCS (CalcCCSN2) and literature infrared multiple photon dissociation (IRMPD) spectroscopy. As expected, all cationized species here form charge solvated structures in the gas phase. Imidacloprid coordinates all three cations at the pyridinic N, with a varying degree of nitroguanidine non-covalent interaction for each, depending on the cation. Sodiated and potassiated imidacloprid ions have a 10-membered ring structure where the overall size trend depends more on the non-covalent interaction with nitroguanidine than the incorporated cation size, resulting in different structures. Chlorpyrifos also coordinates cations at the N, but consistently forms 6-membered ring structures. Sodiated and potassiated species change in size relative to the size of the incorporated cation. The consistency of interlaboratory results and current results also support confident assignment for the protomer of [chlorpyrifos + H]+.