Ligand Preferences of Divalent Main‐Group and Transition Metal Ions

Journal of Mass Spectrometry, Volume 61, Issue 11, November 2026.

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Assessing the use of ASAP‐MS for Screening a UK Pub for Illicit Drug Substances

Journal of Mass Spectrometry, Volume 61, Issue 11, November 2026.

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A Metabolomics and Network Pharmacology Approach Using LC–MS to Investigate the Mechanisms of Fufang Ejiao Jiang in Treating Chemotherapy‐Induced Myelosuppression

ABSTRACT Objective This study aimed to investigate the mechanism and pharmacologically active compounds of Fufang Ejiao Jiang (FFEJJ) in the prevention and treatment of myelosuppression after chemotherapy (MAC) through a combination of serum metabolomics and network pharmacology. Methods Sprague Dawley rats were randomly assigned to three groups: the blank group, the model group, and the FFEJJ group (10.8 g/kg). A MAC rat model was induced using cyclophosphamide. Simultaneously with model establishment, rats were intragastrically administered once daily for 15 consecutive days. The routine blood parameters of the rats were measured, and pathological changes in the spleen and bone marrow were observed. Nontargeted serum metabolomics was employed to identify differential metabolites associated with MAC and their related pathways. Liquid chromatography-mass spectrometry (LC–MS) was used to analyze the chemical composition of FFEJJ, and its mechanism and pharmacologically active compounds in the treatment of MAC were further predicted using network pharmacology. Results FFEJJ significantly improved the hematopoietic function of bone marrow in the MAC model rats. Compared to the blank group, the model group exhibited obvious spleen injury and bone marrow disorder, with noticeable fatty infiltration in the bone marrow cavity. Following FFEJJ treatment, the condition of spleen tissue and bone marrow in MAC rats was significantly improved. Serum metabolomics analysis of endogenous metabolites identified 14 differential metabolites associated with the MAC mechanism in both positive and negative ion modes, primarily involving pathways such as aminoacyl-tRNA biosynthesis, primary bile acid biosynthesis, and unsaturated fatty acid biosynthesis. Using LC–MS, 31 components were identified in FFEJJ. Network pharmacology predictions suggest that the potential pharmacologically active compounds of FFEJJ in the treatment of MAC include apigenin, oleanolic acid, maslinic acid, and azelaic acid. The underlying mechanism may be partly associated with the phosphatidylinositol 3-kinase/serine-threonine kinase (PI3K-Akt) signaling pathway. Conclusion FFEJJ promotes hematopoietic recovery in MAC rats, likely by regulating endogenous metabolic disorders. Apigenin, oleanolic acid, maslinic acid, and azelaic acid are predicted to be multitarget active compounds, with PI3K-Akt signaling as a candidate pathway.

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Integrating Ion Mobility-Resolved Tandem Mass Spectrometry and Microcrystal Electron Diffraction for Structural Elucidation

AbstractDetermining the three-dimensional structures of small molecules in complex mixtures remains challenging as current approaches typically require physical isolation and quantities of material that are excessive for many components. Here we present a reciprocal structure-determination strategy that integrates ion mobility-resolved high-resolution tandem mass spectrometry (IMS-HRMS-MS/MS) with microcrystal electron diffraction (MicroED/3DED), enabling chemically consistent three-dimensional structure elucidation from sub-microgram quantities of material. Analysis of synthetic reaction mixtures revealed multiple stereoisomeric products with distinct ion-mobility and fragmentation behaviour. Mechanistically grounded modelling of fragmentation pathways and collision cross sections constrained viable three-dimensional molecular geometries, while MicroED independently resolved the structure of a crystallographically accessible isomer. Crucially, the gas-phase-derived geometries served directly as molecular replacement search models for MicroED, including for a second reaction product whose diffraction data could not be solved by direct methods alone, thereby demonstrating direct transfer of structural information between mass spectrometry and electron diffraction. Together, IMS-HRMS-MS/MS and MicroED provide complementary structural projections whose integrated interpretation enables structure elucidation of small molecules directly from complex heterogeneous mixtures using minimal amounts of material.

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A monoallelic immunopeptidome atlas of 10 prevalent canine DLA-88 alleles

Characterization of naturally processed MHC class I (MHC-I)-bound peptides is essential for defining allele-specific peptide-binding features and understanding the functional consequences of MHC-I polymorphism. However, immunopeptidome analyses of dog leukocyte antigen (DLA) class I (DLA-I) molecules remain limited and comprehensive monoallelic ligand datasets for prevalent DLA-88 alleles are still lacking. Here, we established canine melanoma-derived cell populations expressing individual functional DLA-88 alleles and generated a monoallelic immunopeptidome atlas of prevalent DLA-88 alleles. Using liquid chromatography-tandem mass spectrometry, we identified 32,702 naturally processed peptides of 7 to15 amino acids across 10 DLA-88 alleles, substantially expanding the available DLA-88 immunopeptidome landscape. These 10 alleles exhibited canonical peptide length distributions and allele-specific binding motifs that reflected variation in binding-groove pseudo-sequences defined from human MHC-I peptide-contact residues. Ligand sharing between DLA-88 alleles was associated with binding site distance. Incorporation of the comprehensively characterized DLA-88 ligand datasets in this study increased by more than fourfold the number of published canine DLA-I alleles with ligand-characterized reference alleles predicted to have similar peptide-binding features. We also found that antigen-processing signatures were highly conserved with those reported in humans. As a proof-of-concept application, we selected 54 DLA-88-bound peptides identified in our immunopeptidome analysis as candidate peptides for canine cancer immunotherapy by evaluating the normal tissue expression profiles of their source proteins. This DLA-88 immunopeptidome atlas provides insights into allele-dependent differences in antigen presentation and represents a valuable resource for developing accurate DLA-88-binding peptide prediction tools and supporting peptide-based immunological studies in dogs.

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Mass spectrometry-based screening for monoclonal gammopathy in individuals undergoing routine physical examinations: Analyses of consecutive 15,068 cases in China

Publication date: Available online 11 October 2026 Source: Clinica Chimica Acta Author(s): Zi-han Yang, Li-xin Wang, Yu-xi Wang, Qian Di, Wei Su, Jian-hua Han, Jian Li

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DTCAMD, a disease-associated truncated form of CRYAB in neovascular age-related macular degeneration: a potential driver of subretinal fibrosis

Abstract Purpose: Subretinal fibrosis causes irreversible vision loss in neovascular age-related macular degeneration (nAMD) and remains poorly controlled by anti-vascular endothelial growth factor (VEGF) therapy. We investigated the role of B-crystallin (CRYAB) in angiogenic and fibrotic pathology and evaluated disease-associated CRYAB truncation as a therapeutic target. Methods: Aqueous humor from patients with nAMD was analyzed by quantitative proteomics and receiver operating characteristic (ROC) analysis. CRYAB function was assessed using knockout and knockdown approaches in a choroidal neovascularization (CNV) mouse model. CRYAB truncation and associated proteins were examined by immunoblotting, co-immunoprecipitation, and liquid chromatography-tandem mass spectrometry (LC-MS/MS). C-terminal truncation was further examined in mouse retinal tissue using antibodies generated against full-length CRYAB and its C-terminal region. Primary human retinal pigment epithelial (hRPE)-THP-1 co-cultures were used to examine CRYAB truncation under fibrosis-associated conditions. Pharmacological effects were tested using ({+/-})-threo-3-methylglutamic acid (T3MG) and 4-(2-aminoethyl)benzenesulfonyl fluoride hydrochloride (AEBSF). Results: CRYAB was upregulated in the aqueous humor of patients with nAMD. Higher CRYAB levels were associated with persistent lesions after initial anti-VEGF treatment. CRYAB knockout or knockdown reduced CNV pathology and decreased VEGFA and -smooth muscle actin (SMA) expression, without a significant substrain effect between C57BL/6N and C57BL/6J mice. A Ser45-phosphorylated truncated CRYAB species was detected in mouse laser-induced CNV model. We termed this species disease-associated truncated CRYAB in AMD (DTCAMD). Peptide mapping showed reproducible loss of distal C-terminal peptide coverage in truncated CRYAB. Consistent with this finding, C-terminal antibody recognition was reduced in CNV lesions. In hRPE-THP-1 co-cultures, DTCAMD accumulated with increased SMA expression. Proteomic analysis identified Prss1 as a candidate CRYAB-associated serine protease linked to truncation under CNV conditions. T3MG and AEBSF reduced DTCAMD-associated signals and CNV pathology. Conclusions: CRYAB contributes to angiogenic and fibrotic pathology in CNV. Disease-associated CRYAB truncation, particularly Ser45-phosphorylated DTCAMD, represents a potential therapeutic target for fibrotic remodeling in nAMD.

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Single Cell Proteomics reveals partial uncoupling of the Glycerol-3-Phosphate shuttle to compensate for Electron Transport Chain dysfunction in Alexander Disease GFAP mutations

Alexander disease (AxD) is a rare genetic leukodystrophy caused by dominant mutations in the gene coding for the astrocytic intermediate filament protein Glial Fibrillary Acidic Protein (GFAP). Understanding disease mechanisms is complicated by the fact that mutant GFAP promotes further GFAP accumulation, making it difficult to distinguish mutation-specific effects from those caused by elevated GFAP levels. Here, we performed mass spectrometry-based single cell proteomics to investigate proteomic alterations associated with increasing levels of wildtype GFAP and a common AxD-causing mutant GFAP R239C. By analyzing individual cells spanning a broad range of GFAP expression levels, we separated dosage-dependent effects from mutation-specific responses. Cells expressing high levels of wildtype GFAP increasingly resembled R239C-expressing cells at the proteomic level, supporting a role for GFAP accumulation in disease pathogenesis. In contrast, mutant GFAP specifically correlated with increased mitochondrial antioxidant enzymes and remodeling of the proteasome tailored toward ATP- and ubiquitin-independent degradation of oxidized proteins. Integration with proteomics data from patient-derived cortical organoids revealed increased abundance of nuclear-encoded mitochondrial proteins and respiratory chain assembly factors without corresponding changes in mitochondrially encoded proteins, suggesting impaired electron transport chain (ETC) assembly. Consistent with this, AxD cells displayed reduced oxygen consumption, increased glycolytic activity, enhanced utilization of the cytosolic part of the glycerol-3-phosphate (G3P) shuttle, and accumulation of triacylglycerides and lipid droplets. We propose that ETC dysfunction promotes partial uncoupling of the G3P shuttle, allowing sustained regeneration of cytosolic NAD to support glycolysis while diverting G3P toward lipid synthesis and storage. By regenerating NAD through the G3P shuttle rather than lactate fermentation, AxD astrocytes may sustain glycolytic flux while preserving lactate production, an important metabolic substrate for neighboring neurons. Together, our findings identify ETC dysfunction as a central feature of AxD and suggest that metabolic adaptation through the G3P shuttle links mitochondrial dysfunction to glycolytic reprogramming and lipid accumulation. More broadly, these results provide new insight into how astrocyte dysfunction drives molecular pathways implicated in neurodegeneration.

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Spatial isotope tracing maps compartmentalized nutrient use across the adult fruit fly

Drosophila melanogaster is a powerful model for studying systemic metabolism. Although metabolism is compartmentalized across tissues, prior work in adult Drosophila has mostly measured it in dissected tissues rather than in situ, limiting the spatial information that can be gained. Here, we combine whole-fly mass-spectrometry imaging with stable-isotope tracing and flux modeling to quantify metabolic activities across the adult fruit fly in a spatially resolved manner. Across 68 tracer-fed Oregon-R female flies and 187,709 pixels, we map 81 metabolites onto eight annotated regions, including muscle, fat body, gut, and nervous system. Glucose labeling and fitted relative fluxes indicate higher glycolytic and tricarboxylic acid cycle turnover in thoracic muscle than in abdominal fat body; proline labels the nervous system and eye; glutamine the abdominal reproductive system and gut. Alanine carries glucose-derived carbon through the hemolymph and transfers nitrogen into glutamate. In flies bearing yorkie-driven gut tumors, alanine contribution to malate rises in gut and abdomen, and reducing gut alanine uptake lowers tumor burden. Together, this work establishes a framework for quantitative spatial metabolic analysis, showing compartmentalized nutrient use across the adult fruit fly.

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Characterization of Full‐Length Antibody Complexes Through HDX‐Mass Spectrometry Coupled With NMR Spectroscopy: New Insight Into Avelumab/PD‐L1 Interaction

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.

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Graphical abstract TOC

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

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Graphical abstract TOC

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

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Unravelling the Deprotonation Isomers of Sulfobenzoic Acid Produced via Electrospray Ionization: A Combined Infrared Spectroscopy and Quantum Chemical Study

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

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onsite: An Integrated Framework for Phosphosite Localization and False Localization Rate Estimation

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.

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Improving Molecular Formula Assignment of Nitrogen- and Sulfur-Rich DOM in Ultrahigh-Resolution Mass Spectrometry: Validation of Oligopeptides

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.

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Proteoform-Resolved Interaction Mapping of Target Protein Complexes in Living Cells via Tracelessly Releasable Cross-Linking

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.

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Chiral Analysis of 2-Hydroxyglutarate in IDH-mut Glioma Tissue using the Kinetic Method

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.

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Extending the separation space in online comprehensive two-dimensional liquid chromatography-mass spectrometry through second-dimension column switching: application to Tamarindus indica L.

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

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Unveiling the Collision-Induced Dissociation Pathways of Protonated PO3G Dimer: An Integrated Energy-Resolved MS and Quantum Chemical Study

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.

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Artificial intelligence-enabled mass spectrometry-based metabolomics: current status and future prospects

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

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Sensitive detection of 4-hydroxy-2-nonenal-modified proteins in oxidative stress-related diseases

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

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Evaluation of a Hydrophilic Interaction Liquid Chromatography Design Space for Amino Acids

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.

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Evaluating a Lightweight Neural Network for Aggregate Isotope Distribution Prediction

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.

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Single-Cell Mass Spectrometry with Enhanced Coverage of cis -Diol Metabolites via a Reactive Pulled Flowprobe in Static-Zone Enrichment Sampling Mode

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.

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xTracer: Integrating Chromatogram and Mobilogram Correlations for Untargeted Peptide Identification in SLIM-Based PAMAF Data

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.

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The Au−TiO 2 Janus Material Enables Integration of Serum Exosome Capture with Palmitoylated and Phosphorylated Peptide Enrichment for Non-Small Cell Lung Cancer Profiling

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.

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A Cooperative Matrix for Enhanced MALDI MSI of Metabolic Alterations Associated with Oxidative Stress in Spinal Cord Injury

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.

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Differentiation of Tetracycline Isomers by Cyclodextrin-Enhanced Ion Mobility-Mass Spectrometry with Computational Insights

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

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Mass Spectrometry‑Based Chemoproteomics for Modern Drug Screening: A Critical Review and the 3M Framework (Match–Map–Mine)

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

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TherMIDAS: An Integrated Data Acquisition System for FT-ICR Mass Spectrometry

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.

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