Abstract. Mass-spectrometry-based single-cell proteomics has evolved from an unconventional idea into a rapidly advancing technology that is opening new pe

Abstract. Mass-spectrometry-based single-cell proteomics has evolved from an unconventional idea into a rapidly advancing technology that is opening new pe

AbstractNative mass spectrometry (nMS) is well established for measuring protein masses and stoichiometries using nanoelectrospray ionization (nESI), yet salt adduction and source activation energies can limit routine measurements. In this study, we benchmark submicron quartz nanopipette nESI emitters (

Abstract. Functional annotation of microbial genes lags behind the pace of genome sequencing, leaving major gaps in our understanding of microbial metaboli

AbstractMass-spectrometry-based single-cell proteomics has evolved from an unconventional idea into a rapidly advancing technology that is opening new perspectives on biology. In this perspective, I reflect on the development of the field over the past decade: the guiding ideas, the early experiments that established feasibility, the advances in sample preparation, mass spectrometry methods, instrumentation, computation, and multiplexing that transformed sensitivity and throughput, and the collaborative efforts that made these technologies increasingly reproducible and accessible. I highlight biological results from the first decade and questions that have become addressable with highly quantitative protein measurements in individual cells, including functional protein coordination, regulation of protein synthesis and degradation, developmental decisions, and disease progression. Looking forward, I foresee that continued technological innovation, rigorous benchmarking, and an open and critically engaged community will be essential for realizing the broader promise of single-cell proteomics: turning high resolution protein analysis into a powerful source of biological insight, including generalizable principles.

AbstractOligodendroglioma is a diffuse glioma defined by IDH mutation and whole-arm 1p/19q codeletion. Although gangliosides play essential roles in membrane organization and tumor biology, their molecular diversity in oligodendrogliomas remains poorly understood because of the limited structural resolution of conventional analytical approaches. Gangliosides extracted from paired tumoral and peritumoral tissues from three patients with oligodendroglioma were analyzed using an integrated workflow combining high-performance thin-layer chromatography (HPTLC) and high-resolution cyclic ion mobility mass spectrometry. Molecular annotation included canonical, O-acetylated, and fucosylated ganglioside species. A total of 205 distinct ganglioside molecular species were identified, providing a detailed molecular-species-level characterization of the gangliosidome in the analyzed oligodendroglioma and matched peritumoral tissue. Tumoral tissues contained 184 species, peritumoral tissues contained 171 species, and 148 species were shared, including a set of 55 ganglioside molecular species detected in all samples. Oligodendroglioma retained a diverse inventory of complex GD-, GT-, GQ-, and GP-series gangliosides together with numerous O-acetylated and fucosylated structures. Despite greater molecular diversity in tumors, the overall ganglioside class distribution and ceramide composition remained largely conserved, indicating that the remodeling process predominantly affects glycan head groups rather than the ceramide scaffold. This study provides the first detailed cyclic ion mobility mass spectrometry (cIMS-MS) characterization of the gangliosidome in isocitrate dehydrogenase (IDH) mutant, 1p/19q-codeleted oligodendroglioma. The findings substantially expand the known molecular diversity of this tumor type and identify selective glycan alterations with the preservation of ceramide architecture as a defining molecular feature, providing a framework for future biomarker discovery and mechanistic studies of glycosphingolipid metabolism in diffuse gliomas.

AbstractTop-down mass spectrometry (TD-MS) allows detailed characterization of biomolecular heterogeneity, e.g., sequence variants, chemical and biological modifications, and mutations. While relatively established in positive-ion mode, negative-ion-mode TD-MS of intact proteins has been less explored, in part due to a lack of suitable activation approaches for tandem mass spectrometry. Here, we show that electron detachment dissociation (EDD) can yield analytically useful sequence coverage up to ∼60% for β-casein (24 kDa), with relatively straightforward spectral interpretation due to favored formation of a• and x-type fragments with limited neutral loss. This leap in EDD performance from previously reported 5% sequence coverage was enabled by use of a custom wide-bore 9.4 T FT-ICR instrument with a solid dispenser cathode for optimal anion-electron overlap. In addition, a prototype─now commercially available─instrument with a dynamically harmonized ICR cell and a hollow cathode yielded 51% sequence coverage for β-casein, more than an order of magnitude higher than previous reports. EDD of phosphorylated α- and β-casein proteins showed phosphate retention in fragment ions and allowed phosphorylation site determination. High-energy, ∼72–92 eV, EDD is demonstrated to enable shorter irradiation times than previously reported, as low as 3 ms for an RNA 18-mer (100% sequence coverage) and 35 ms for carbonic anhydrase (47% sequence coverage), although higher electron energy results in lower average fragment ion charge. Numerous (y – 2H) fragments from backbone cleavage near proline were observed, indicative of electronic excitation under EDD conditions. Electron energy vs irradiation time heatmaps provide an in-depth understanding of how to tune EDD for desired fragmentation outcomes. Overall, the presented results show promise for incorporating EDD in online liquid chromatography-TD-MS workflows.

AbstractLignocellulosic biomass is the most abundant type of renewable feedstock. It can be used to produce bio-oils, often by pyrolysis processes. Depending on the treatment and feedstocks used, the bio-oils obtained present very different molecular compositions, influencing their upgrading process into biofuels. As they are highly complex mixtures, their molecular characterizations are challenging. One way, among others, is to probe their molecular level by using direct infusion in Fourier transform ion cyclotron mass spectrometry (FTICR MS). However, mass spectrometry alone cannot discriminate between isomers, and a loss of information because of ionization competition can be observed. Hyphenation of liquid chromatography (LC) with FTICR MS can afford an efficient solution to these issues but requires compromises, mainly on the MS side. In this work, we evaluated the performance of a new 18 T FTICR MS coupled to reversed-phase liquid chromatography for the characterization of bio-oils. Using representative standards of different molecular families (carbohydrates, polyphenols, acids, etc), a method adapted to bio-oils was developed in LC-FTICR MS. The coupling demonstrated the high mass-accuracy stability of FTICR MS even under high total ion current variations and revealed the very high isomeric complexity of bio-oils. Additionally, the coupling reduced ionization competition, enabling the detection of compounds that could not be detected by direct injection. Finally, four bio-oils were compared to highlight the interest of the proposed method.

AbstractSpectra from tandem mass spectrometry (MS/MS) of intact proteins are often highly complex, containing numerous closely spaced peaks arising from fragment ions with similar m/z values. This high level of spectral density continues to challenge even state-of-the-art high-resolution mass spectrometers, particularly as protein size increases. Here, we show that this complexity can produce a misleading spectral interference pattern when dissociating proteins whose fragment ions exhibit a sufficiently linear relationship between fragment mass and mass defect. In such cases, isotopic m/z peaks from multiple fragment ions constructively overlap to produce a series of predominantly ∼1 m/z-spaced peaks, which we refer to as a “picket-fence” pattern. These peaks are easily misinterpreted as signals from much lower mass fragment ions (“peak at every mass” background) or distort expected isotopic peak envelopes. More fundamentally, these picket fence peaks can be understood as the collective manifestation of a high spectral density of signals arising from both sequence ions and the aggregate contribution of numerous individually low-abundance internal fragment ions. Recognizing and accounting for this often-observed phenomenon is essential for accurate fragment-ion assignment and interpretation of intact protein MS/MS spectra.

AbstractProtonation isomers (protomers) are structural isomers that differ in the location site of a proton (H+). In mass spectrometry, an understanding of the fundamentals of analyte protonation is essential as the site of protonation influences many gas-phase ion properties, including ion stability, ion fragmentation yields and products, ion–molecule reactivity, photochemistry, conformation, and chirality. If ignored, the presence of protomers can confound the detection and assignment of analyte ions and can also reduce peak loading under many mass spectrometry workflows. In this perspective, we outline how small-molecule protomers arise and discuss the competing mechanisms that govern their relative populations, this implicates electrospray droplet desolvation, ion source reactions, proton-bound dimer stability, ion–molecule reactions, collision-induced internal proton transfer, and photoinduced internal proton transfer. Key concepts are summarized and frontiers for charge-site management are proposed, including deprotonation isomers, metal cations, and multiply charged species.

AbstractExtensive characterization of xenobiotic metabolites remains a major challenge in mass spectrometry-based exposomics, as untargeted high-resolution mass spectrometry (HRMS) can detect extensive chemical diversity but often lacks sufficient structural annotation and prioritization strategies for unknown metabolites. Here, we developed a built-for-purpose HRMS-based workflow combining untargeted metabolomics, in silico metabolite prediction, structural annotation, and toxicity prioritization to characterize xenobiotic biotransformation products using Disperse Orange 61 (DO61) as a case study. Sprague–Dawley rats were exposed to DO61 via oral gavage, and liver, plasma, and urine samples were analyzed by ultra-high performance liquid chromatography (UHPLC) coupled to HRMS in positive and negative ionization modes. Statistically significant features were prioritized and screened against a BioTransformer-generated suspect library containing predicted Phase I, Phase II, reductive, and microbial transformations. HRMS-based annotation, supported by bromine isotope pattern analysis and MS/MS fragmentation, identified putative DO61 metabolites, while SIRIUS-derived molecular formula predictions provided additional confidence through fragmentation-based structural evaluation. The workflow experimentally confirmed reductive azo cleavage as an early DO61 transformation, producing two aromatic amine products, and revealed extensive downstream metabolism of the parent compound and both cleavage products. Computational toxicity prediction further prioritized confirmed and putatively annotated metabolites with potential mutagenic relevance for a future evaluation. This workflow demonstrates how integrating untargeted HRMS with computational approaches can facilitate metabolite discovery, improve structural annotation confidence, and prioritize metabolites for toxicological evaluation, providing a hypothesis discovery strategy for characterizing xenobiotic metabolism and supporting exposure and hazard assessment within the field of exposomics research.

AbstractYersinia pestisundergoes dramatic physiological changes as it transitions from its flea vector (∼20–30 °C) to mammalian hosts (37 °C), including remodeling of its cell envelope lipids to evade innate immunity and enhance virulence. While various temperature-dependent changes in this organism have been previously documented, the broader lipidome remains poorly characterized. We applied liquid chromatography coupled with ion mobility spectrometry and tandem mass spectrometry (LC-IMS-MS/MS), in addition to ozone-induced dissociation (OzID), to comprehensively profile lipids in three attenuated Y. pestis strains (A1122, KIM D27, and KIM D1) grown at 30 and 37 °C. Untargeted lipidomic analysis identified 97 lipids across multiple classes, with principal component analysis revealing temperature-dependent clustering patterns distinct from strain-specific variations. Comparison of lipid profiles between temperatures revealed many significantly differentially expressed lipids per strain, with most strain-specific responses rather than shared across all strains. OzID fragmentation successfully identified double-bond positions for common unsaturated fatty acids and lysophospholipids, also enabling structural discrimination between monounsaturated and cyclopropyl fatty acid isomers. Notably, lipids containing cyclopropyl fatty acids were significantly upregulated at 37 °C across all three strains, suggesting a conserved temperature-responsive mechanism for enhancing membrane stability during mammalian host infection. Our study demonstrates that comprehensive, high-detailed, structurally resolved lipidomics reveals temperature-dependent lipid remodeling characteristics in Y. pestis that may support host transition and virulence, with potential applications for identifying lipid biomarkers.

AbstractThe human heart is characterized by aberrant lipid accumulation and remodeling during periods of stress and disease, yet spatially resolved lipidomic profiling of the human heart remains unreported. Here, we employ matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI) to map lipid distributions across five anatomical regions of healthy human donor hearts (left and right atrium, left and right ventricle, and interventricular septum). Cryosections of donor hearts from healthy subjects were thaw-mounted onto indium tin oxide slides, coated with 2,5-dihydroxyacetophenone, and analyzed on a Bruker timsTOF fleX mass spectrometer in positive and negative ionization modes (m/z 50–1850; 20 μm raster spacing). Serial sections were stained with hematoxylin and eosin to enable histological coregistration with lipid distributions. We identified 150 unique lipid species across four glycerophospholipid classes, including phosphatidylcholine (PC), phosphatidylglycerol (PG), phosphatidylethanolamine (PE), and phosphatidylserine (PS), with abundances and spatial distributions differing significantly between regions. H&E coregistration further resolved epicardial and myocardial compartments, enabling tissue-specific lipid mapping. These findings establish the first spatially resolved lipidomic profiles of the human heart and provide a framework for identifying region-specific lipid biomarkers of cardiovascular disease.

AbstractKinetic energy distributions (KEDs) of secondary ions encode information about ion formation in secondary-ion mass spectrometry (SIMS), yet are typically interpreted on a per-ion basis without a unifying framework. In the MeV-SIMS regime, where sputtering is governed by electronic excitation within a transient ion track, the diversity of KED shapes reflects a complex and heterogeneous emission environment. Within this paper, we analyze an extensive data set of KEDs for atomic and molecular ions, including protonated, deprotonated, and cationized species of various organic molecules, using non-negative matrix factorization (NMF). We show how the data set of measured samples can be well described by three characteristic components. Dimensionality analysis demonstrates that three components provide the minimal description of the data, and the result is robust with respect to two different reconstructions of KEDs from yield–reflectron-voltage measurements. Mapping ion-specific weights in this three-component space can reveal systematic trends in KED fingerprints. Protonated ions are confined to the positive-energy regimes, whereas deprotonated ions exhibit a significant contribution from the negative-energy component, indicating additional reorganization processes. Atomic ions display a mass-dependent redistribution between the two positive-energy regimes, while the KED of cationized molecular ions is well aligned with the KED of the corresponding cation, especially for alkali metals. The three-component representation, therefore, provides a unified description of secondary-ion KEDs and is most likely consistent with emission under varying excitation conditions within the ion track. These results establish a direct link between kinetic energy distributions and ion formation pathways, offering a general framework for interpreting SIMS data across different ion classes and molecular systems.

AbstractUtilizing picosecond infrared laser mass spectrometry (PIRL-MS), we set out to determine the limit of tumor infiltration detection offered by this ambient ion source. Using murine models of brain cancer subjected to handheld PIRL-MS, as well as spatially resolved PIRL-MS imaging and various tissue models, we estimated the limit of tumor infiltration detection to be approximately 15% using physically combined glioblastoma tissue sections and approximately 4% using computational pixel mixing of orthotopic medulloblastoma imaging data. These estimates are broadly consistent in magnitude with independent iKnife-REIMS studies that employed different sampling methods and experimental models. At these detection limits, PIRL-MS predicted positive margins with a sensitivity of 84.21% and a specificity of 86.43%. This observation is based on the analysis of n = 38 orthotopic glioblastoma murine tissue sections bearing various tumor ranges and utilized n = 178 classifiable mass spectral data points. As a proof-of-principle study, these estimates derive from a limited number of biological replicates, including n = 3 subcutaneous xenografts used to construct the tissue model, n = 5 orthotopic animals for validation, and n = 2 tumors underlying the imaging-based estimate and, therefore, should be regarded as preliminary rather than definitive detection limits. These findings highlight the potential of PIRL-MS as a rapid, label-free intraoperative tool for margin assessment and provide insight into the practical limits of tumor infiltration detection in heterogeneous brain tumors.

AbstractTrispecific antibodies (TriAbs) integrate multiple antigen-binding modules within a single construct, creating greater architectural complexity and conformational heterogeneity than conventional monoclonal antibodies. Conventional stability measurements report ensemble-averaged behavior and may therefore conceal stability differences among distinct conformational subpopulations within a TriAbs construct. Here, tandem-trapped ion mobility spectrometry (Tandem-TIMS) was combined with differential melting voltage (DMV) analysis to investigate the conformation-resolved gas-phase stability of wild-type and Fc-mutated TriAbs. Under native conditions, both antibody constructs retained compact, native-like structures with nearly identical ensemble-level cross sections. Nonensemble Tandem-TIMS measurements resolved distinct conformational subpopulations that followed different activation-induced unfolding trajectories, confirming that they represented structurally distinct conformational states. DMV analysis quantified these differences using a single, quantifiable metric: the melting voltage, Vm. The wild-type construct showed a stepwise increase in the melting voltage, with several conformational subpopulations displaying comparable relative stability toward collisional activation. In contrast, the AAS-mutated construct exhibited a more gradual increase in stability with increasing cross section. These differences were not apparent from the ensemble-level cross section distributions and were only weakly reflected in solution-phase nanoDSF measurements. The results demonstrate that similar intact antibody size and bulk thermal properties do not necessarily imply similar conformational landscapes. Most importantly, the integration of Tandem-TIMS with DMV analysis provides a nonensemble strategy for directly connecting structural heterogeneity with the relative gas-phase stability of conformational subpopulations in complex antibody therapeutics.

AbstractElectrospray ionization mass spectrometry (ESI-MS) is a standard and robust technique for analysis of a large variety of biomolecules. Direct infusion approaches offer rapid, high-throughput analysis of small sample volumes but are inherently susceptible to matrix effects during electrospray ionization. These matrix effects can substantially alter analyte ionization and gas-phase response and thereby complicate the interpretation of analyte abundances in complex biological samples. Herein, we developed a titration-based workflow to identify matrix effects and distinguish true changes in endogenous analyte abundance from ionization artifacts using direct infusion probe mass spectrometry (DIP-MS). Rat brain tissue extracts, rat insulinoma cell extracts, and isotopically labeled internal standards were used to model different matrix complexities to define condition-based differences in matrix effects. Thereafter, by mixing paired extracts in different ratios and fitting linear regression models, we assessed analyte-specific responses to sample-specific matrices. Moreover, we uncovered ion suppression or enhancement of hundreds of analytes by comparing regression slopes using interaction tests. We find that using endogenous analytes in our titration-based workflow gives a good indication of matrix effects for certain analyte classes. However, using a preselected panel of internal standards is strongly favorable for reliably identifying matrix effects during ionization. Altogether, combining our titration workflow, a selected panel of internal standards, and regression modeling provides a sensitive way of detecting matrix effects and for distinguishing true metabolite abundance changes from ionization artifacts.

AbstractEnantiomers continue to represent a significant analytical challenge despite their importance in biological and pharmaceutical analyses. Established approaches (e.g., chiral chromatography) frequently require specialized chiral stationary phases, selectors, or extended separation times. Ion mobility spectrometry (IMS) offers a rapid alternative; however, the collision cross sections (CCS) of enantiomers are identical and therefore preclude separation. In the present work, we demonstrate a simple chiral derivatization strategy for small drug enantiomers. Specifically, Mosher’s chloride is used to interrogate (R/S)-amphetamine and methamphetamine with a total time (reaction and analysis) of less than 2 min. The resulting products are baseline-resolved using structures for lossless ion manipulations (SLIM) high-resolution ion mobility-mass spectrometry (HRIM-MS), despite CCS differences of less than 1.9 and 1.2%, respectively. Conventional reversed-phase liquid chromatography (RP-LC) confirms the purity of the products, as evidenced by the extracted mobility spectra. Finally, the method allowed determination of enantiomeric excess (ee), with a strong linear correlation between prepared and measured values. More broadly, covalent chiral derivatization provides a readily accessible strategy for encoding stereochemical information into analytes prior to rapid gas-phase differentiation.

AbstractUntargeted liquid chromatography–high-resolution mass spectrometry (LC–HRMS) supports high-throughput metabolomics, but rapid gradients can compress chromatographic separation and limit downstream annotation. A practical annotation strategy is to analyze all samples using a rapid untargeted method and then reinject selected biological and pooled quality-control (QC) samples under a longer-gradient method to improve separation, MS/MS acquisition, and standard-based confirmation. Because short- and long-gradient feature tables cannot be matched reliably by m/z alone, we developed RTBridge, a same-sample, feature-table-based retention-time (RT) bridging workflow that establishes feature correspondence without requiring structural descriptors or quantitative structure–retention relationship models. Unique anchors were selected using within-method mass uniqueness, cross-method mass agreement, and an abundance-concordance score (ACS). Six empirical RT-transfer models were evaluated: linear regression, piecewise linear interpolation, locally estimated scatterplot smoothing (LOESS), piecewise cubic Hermite interpolation (PCHIP), spline/generalized additive modeling (GAM), and monotone GAM. Using all selected mode-specific anchors, PCHIP produced 5,595 primary feature pairs across four matrix/mode data sets, with a mean median RT error of 0.0232 min. GAM-based residual screening reduced the number of selected training anchors from 1,518 to 1,185, primary-pair recovery from 5,595 to 4,867, and verification support from 161 to 151, while decreasing the mean median RT error to 0.0212 min. We therefore recommend PCHIP RT transfer using all selected mode-specific anchors without residual-based hard deletion, followed by abundance-concordance ranking. RTBridge establishes feature correspondence rather than metabolite identification. Potential extensions include platform or column transfer, batch harmonization, cross-matrix correspondence, and interlaboratory integration but will require direct experimental validation.

AbstractMore than one-half of the world’s plastic waste comes from poorly recyclable polymers, such as polyethylene and polypropylene. The increased accumulation of plastic waste is a growing environmental challenge. This led to the employment of polyesters with controlled degradation behavior for a variety of materials applications. Understanding the relationship between polymer structure and fragmentation pathways is essential for designing materials that balance durability and sustainability. Polyesters and polyamides with an Cα adjacent to the carbonyl, fragment via 1,5- and 1,3-hydrogen rearrangements; however, the fragmentation of a polyester where an is not present adjacent to the carbonyl has not been researched thoroughly. This work reports the first detailed characterization of the fragmentation behavior of both linear and cyclic poly(dimethylpropanoate) (poly(DMP)). Poly(DMP) possesses a neopentyl carbon which slows degradation and inhibits the typical 1,5-hydrogen rearrangements common in other polyesters. Cyclic poly(DMP) undergoes ring opening at various points before fragment generation, resulting in a mixture of ring-opened linear species, while the linear polymer predominantly fragments through single-bond cleavages. Additionally, the fragmentation patterns are influenced by poly(DMP) end groups, with distinct patterns observed for hydroxyl-terminated, halogen-terminated, and pyridinium-initiated polymers. Moreover, ion mobility mass spectrometry (IM-MS) effectively distinguishes isomeric fragments in cyclic poly(DMP) based on the differences in the collision cross-section of cyclic precursor and the resulting linear fragment ions.

AbstractGas chromatography–mass spectrometry (GC–MS) is widely applied to wound-associated volatile organic compounds (VOCs), yet the preanalytical steps that govern its sensitivity remain poorly characterized, limiting comparison across studies of diabetic foot ulcer (DFU) infection. We benchmark a controlled solvent-based extraction workflow with direct internal-standard addition for GC–MS profiling of clinical DFU swabs. A six-compound multiclass panel (butanoic acid, 3-methyl-; 1-octen-3-ol; nonanal; 5-hepten-2-one, 6-methyl-; dimethyl disulfide; and heptane) was spiked onto sterile cotton swabs with toluene-d8 as an internal standard (IS). At day 0, diethyl ether (DE) gave the highest IS-normalized response for every analyte (F(2,6) = 12.4–131.0), most markedly for hydrogen-bond-active species. A 50% nitrogen blowdown step produced volatility-dependent enhancement the lowest enrichment in every solvent (1.0–1.9-fold), whereas high-boiling analytes exceeded 2-fold in DE. Frozen storage at −20 °C for 15 days preserved the IS-normalized response within ±20% of day 0 for most analyte–solvent combinations; hexane gave the tightest precision (mean %RSD 2.3–8.0%), whereas DE was poor for heptane (25.7%). Applied to 28 infected DFUs, the workflow returned 13 VOCs meeting combined retention index (|ΔRI| ≤35) and spectral-library (match factor ≥75) criteria, spanning fatty acids, fermentation products, host lipid-peroxidation aldehydes, phenylalanine catabolites, and palmitamide. These class-stratified preanalytical benchmarks provide an analytical baseline against which clinical wound-VOC studies can be designed and compared.

AbstractTandem mass spectrometry (MS/MS) spectral matching is increasingly performed at the repository scale, where tools such as MASST enable a query spectrum to be compared against heterogeneous public data. Unlike analogous genomic-based searches, repository-scale MS/MS matching lacks integrated false discovery rate (FDR) reporting, leaving parameter selection entirely to user discretion. Here, we evaluate how acquisition factors and analysis filters jointly affect MS/MS matching using a curated library of 40 metabolites spanning ten chemical classes. In this study, we find that normalized collision energies from 30 to 50% balance sufficient fragmentation against loss of larger diagnostic ions, producing the most structurally informative spectra and yielding the highest proportion of repository matches. Using a fragmentation-based decoy library, we show that six minimum matching peaks achieve