Top-down mass spectrometry of native proteoforms and their complexes: a community study.

The combination of native electrospray ionization with top-down fragmentation in mass spectrometry (MS) allows simultaneous determination of the stoichiometry of noncovalent complexes and identification of their component proteoforms and cofactors. Although this approach is powerful, both native MS and top-down MS are not yet well standardized, and only a limited number of laboratories regularly carry out this type of research. To address this challenge, the Consortium for Top-Down Proteomics initiated a study to develop and test protocols for native MS combined with top-down fragmentation of proteins and protein complexes across 11 instruments in nine laboratories. Here we report the summary of the outcomes to provide robust benchmarks and a valuable entry point for the scientific community.

Evaluating protein cross-linking as a therapeutic strategy to stabilize SOD1 variants in a mouse model of familial ALS.

Mutations in the gene encoding Cu-Zn superoxide dismutase 1 (SOD1) cause a subset of familial amyotrophic lateral sclerosis (fALS) cases. A shared effect of these mutations is that SOD1, which is normally a stable dimer, dissociates into toxic monomers that seed toxic aggregates. Considerable research effort has been devoted to developing compounds that stabilize the dimer of fALS SOD1 variants, but unfortunately, this has not yet resulted in a treatment. We hypothesized that cyclic thiosulfinate cross-linkers, which selectively target a rare, 2 cysteine-containing motif, can stabilize fALS-causing SOD1 variants in vivo. We created a library of chemically diverse cyclic thiosulfinates and determined structure-cross-linking-activity relationships. A pre-lead compound, "S-XL6," was selected based upon its cross-linking rate and drug-like properties. Co-crystallographic structure clearly establishes the binding of S-XL6 at Cys 111 bridging the monomers and stabilizing the SOD1 dimer. Biophysical studies reveal that the degree of stabilization afforded by S-XL6 (up to 24°C) is unprecedented for fALS, and to our knowledge, for any protein target of any kinetic stabilizer. Gene silencing and protein degrading therapeutic approaches require careful dose titration to balance the benefit of diminished fALS SOD1 expression with the toxic loss-of-enzymatic function. We show that S-XL6 does not share this liability because it rescues the activity of fALS SOD1 variants. No pharmacological agent has been proven to bind to SOD1 in vivo. Here, using a fALS mouse model, we demonstrate oral bioavailability; rapid engagement of SOD1G93A by S-XL6 that increases SOD1G93A's in vivo half-life; and that S-XL6 crosses the blood-brain barrier. S-XL6 demonstrated a degree of selectivity by avoiding off-target binding to plasma proteins. Taken together, our results indicate that cyclic thiosulfinate-mediated SOD1 stabilization should receive further attention as a potential therapeutic approach for fALS.

Raf promotes dimerization of the Ras G-domain with increased allosteric connections.

Ras dimerization is critical for Raf activation. Here we show that the Ras binding domain of Raf (Raf-RBD) induces robust Ras dimerization at low surface densities on supported lipid bilayers and, to a lesser extent, in solution as observed by size exclusion chromatography and confirmed by SAXS. Community network analysis based on molecular dynamics simulations shows robust allosteric connections linking the two Raf-RBD D113 residues located in the Galectin scaffold protein binding site of each Raf-RBD molecule and 85 Å apart on opposite ends of the dimer complex. Our results suggest that Raf-RBD binding and Ras dimerization are concerted events that lead to a high-affinity signaling complex at the membrane that we propose is an essential unit in the macromolecular assembly of higher order Ras/Raf/Galectin complexes important for signaling through the Ras/Raf/MEK/ERK pathway.

massNet: integrated processing and classification of spatially resolved mass spectrometry data using deep learning for rapid tumor delineation.

MOTIVATION: Mass spectrometry imaging (MSI) provides rich biochemical information in a label-free manner and therefore holds promise to substantially impact current practice in disease diagnosis. However, the complex nature of MSI data poses computational challenges in its analysis. The complexity of the data arises from its large size, high-dimensionality and spectral nonlinearity. Preprocessing, including peak picking, has been used to reduce raw data complexity; however, peak picking is sensitive to parameter selection that, perhaps prematurely, shapes the downstream analysis for tissue classification and ensuing biological interpretation. RESULTS: We propose a deep learning model, massNet, that provides the desired qualities of scalability, nonlinearity and speed in MSI data analysis. This deep learning model was used, without prior preprocessing and peak picking, to classify MSI data from a mouse brain harboring a patient-derived tumor. The massNet architecture established automatically learning of predictive features, and automated methods were incorporated to identify peaks with potential for tumor delineation. The model's performance was assessed using cross-validation, and the results demonstrate higher accuracy and a substantial gain in speed compared to the established classical machine learning method, support vector machine. AVAILABILITY AND IMPLEMENTATION: https://github.com/wabdelmoula/massNet. The data underlying this article are available in the NIH Common Fund's National Metabolomics Data Repository (NMDR) Metabolomics Workbench under project id (PR001292) with http://dx.doi.org/10.21228/M8Q70T. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Best practices and benchmarks for intact protein analysis for top-down mass spectrometry.

One gene can give rise to many functionally distinct proteoforms, each of which has a characteristic molecular mass. Top-down mass spectrometry enables the analysis of intact proteins and proteoforms. Here members of the Consortium for Top-Down Proteomics provide a decision tree that guides researchers to robust protocols for mass analysis of intact proteins (antibodies, membrane proteins and others) from mixtures of varying complexity. We also present cross-platform analytical benchmarks using a protein standard sample, to allow users to gauge their proficiency.

Increasing Top-Down Mass Spectrometry Sequence Coverage by an Order of Magnitude through Optimized Internal Fragment Generation and Assignment.

A major limitation of intact protein fragmentation is the lack of sequence coverage within proteins' interiors. We show that collisionally activated dissociation (CAD) produces extensive internal fragmentation within proteins' interiors that fill the existing gaps in sequence coverage, including disulfide loop regions that cannot be characterized using terminal fragments. A barrier to the adoption of internal fragments is the lack of methods for their generation and assignment. To provide these, we explore the effects of protein size, mass accuracy, internal fragment size, CAD activation energy, and data preprocessing upon the production and identification of internal fragments. We also identify and mitigate the major source of ambiguity in internal fragment identification, which we term "frameshift ambiguity." Such ambiguity results from sequences containing any "middle" portion surrounded by the same composition on both termini, which upon fragmentation can produce two internal fragments of identical mass, yet out of frame by one or more amino acids (e.g., TRAIT producing TRAI or RAIT). We show that such instances permit the a priori assignment of the middle sequence portion. This insight and our optimized methods permit the unambiguous assignment of greater than 97% of internal fragments using only the accurate mass. We show that any remaining ambiguity in internal fragment assignment can be removed by consideration of fragmentation propensities or by (pseudo)-MS3. Applying these methods resulted in a 10-fold and 43-fold expanded number of identified ions, and a concomitant 7- and 16-fold increase in fragmentation sites, respectively, for native and reduced forms of a disease-associated SOD1 variant.

Cyclic Thiosulfinates as a Novel Class of Disulfide Cleavable Cross-Linkers for Rapid Hydrogel Synthesis.

We recently reported that cyclic thiosulfinates are cysteine selective cross-linkers that avoid the "dead-end" modifications that contribute to other cross-linkers' toxicity. In this study, we generalize the chemistry of cyclic thiosulfinates to that of thiol selective cross-linking and apply them to the synthesis of hydrogels. Thiol-functionalized four-arm poly(ethylene glycol) and hyaluronic acid monomers were cross-linked with 1,2-dithiane-1-oxide to form disulfide cross-linked hydrogels within seconds. The synthesized hydrogel could be reduced with physiological concentrations of glutathione, which modulated hydrogel mechanical properties and degradation kinetics. Bovine serum albumin protein was successfully encapsulated in hydrogel, and diffusion-mediated release was demonstrated in vitro. Hep G2 cells grew in the presence of preformed hydrogel and during hydrogel synthesis, demonstrating acceptable cytotoxicity. We encapsulated cells within a hydrogel and demonstrated cell growth and recovery up to 10 days, with and without cell adhesion peptides. In summary, we report cyclic thiosulfinates as a novel class of cross-linkers for the facile synthesis of biodegradable hydrogels.

How many human proteoforms are there?

Despite decades of accumulated knowledge about proteins and their post-translational modifications (PTMs), numerous questions remain regarding their molecular composition and biological function. One of the most fundamental queries is the extent to which the combinations of DNA-, RNA- and PTM-level variations explode the complexity of the human proteome. Here, we outline what we know from current databases and measurement strategies including mass spectrometry-based proteomics. In doing so, we examine prevailing notions about the number of modifications displayed on human proteins and how they combine to generate the protein diversity underlying health and disease. We frame central issues regarding determination of protein-level variation and PTMs, including some paradoxes present in the field today. We use this framework to assess existing data and to ask the question, "How many distinct primary structures of proteins (proteoforms) are created from the 20,300 human genes?" We also explore prospects for improving measurements to better regularize protein-level biology and efficiently associate PTMs to function and phenotype.

Genetically Encoded Fluorescent Proteins Enable High-Throughput Assignment of Cell Cohorts Directly from MALDI-MS Images.

Matrix-assisted laser desorption/ionization (MALDI) mass spectrometry imaging (MSI) provides a unique in situ chemical profile that can include drugs, nucleic acids, metabolites, lipids, and proteins. MSI of individual cells (of a known cell type) affords a unique insight into normal and disease-related processes and is a prerequisite for combining the results of MSI and other single-cell modalities (e.g. mass cytometry and next-generation sequencing). Technological barriers have prevented the high-throughput assignment of MSI spectra from solid tissue preparations to their cell type. These barriers include obtaining a suitable cell-identifying image (e.g. immunohistochemistry) and obtaining sufficiently accurate registration of the cell-identifying and MALDI-MS images. This study introduces a technique that overcame these barriers by assigning cell type directly from mass spectra. We hypothesized that, in MSI from mice with a defined fluorescent protein expression pattern, the fluorescent protein's molecular ion could be used to identify cell cohorts. A method was developed for the purification of enhanced yellow fluorescent protein (EYFP) from mice. To determine EYFP's molecular mass for MSI studies, we performed intact mass analysis and characterized the protein's primary structure and post-translational modifications through various techniques. MALDI-MSI methods were developed to enhance the detection of EYFP in situ, and by extraction of EYFP's molecular ion from MALDI-MS images, automated, whole-image assignment of cell cohorts was achieved. This method was validated using a well-characterized mouse line that expresses EYFP in motor and sensory neurons and should be applicable to hundreds of commercially available mice (and other animal) strains comprising a multitude of cell-specific fluorescent labels.

Automatic 3D Nonlinear Registration of Mass Spectrometry Imaging and Magnetic Resonance Imaging Data.

Multimodal integration between mass spectrometry imaging (MSI) and radiology-established modalities such as magnetic resonance imaging (MRI) would allow the investigations of key questions in complex biological systems such as the central nervous system. Such integration would provide complementary multiscale data to bridge the gap between molecular and anatomical phenotypes, potentially revealing new insights into molecular mechanisms underlying anatomical pathologies presented on MRI. Automatic coregistration between 3D MSI/MRI is a computationally challenging process due to dimensional complexity, MSI data sparsity, lack of direct spatial-correspondences, and nonlinear tissue deformation. Here, we present a new computational approach based on stochastic neighbor embedding to nonlinearly align 3D MSI to MRI data, identify and reconstruct biologically relevant molecular patterns in 3D, and fuse the MSI datacube to the MRI space. We demonstrate our method using multimodal high-spectral resolution matrix-assisted laser desorption ionization (MALDI) 9.4 T MSI and 7 T in vivo MRI data, acquired from a patient-derived, xenograft mouse brain model of glioblastoma following administration of the EGFR inhibitor drug of Erlotinib. Results show the distribution of some identified molecular ions of the EGFR inhibitor erlotinib, a phosphatidylcholine lipid, and cholesterol, which were reconstructed in 3D and mapped to the MRI space. The registration quality was evaluated on two normal mouse brains using the Dice coefficient for the regions of brainstem, hippocampus, and cortex. The method is generic and can therefore be applied to hyperspectral images from different mass spectrometers and integrated with other established in vivo imaging modalities such as computed tomography (CT) and positron emission tomography (PET).

ProForma: A Standard Proteoform Notation.

The Consortium for Top-Down Proteomics (CTDP) proposes a standardized notation, ProForma, for writing the sequence of fully characterized proteoforms. ProForma provides a means to communicate any proteoform by writing the amino acid sequence using standard one-letter notation and specifying modifications or unidentified mass shifts within brackets following certain amino acids. The notation is unambiguous, human-readable, and can easily be parsed and written by bioinformatic tools. This system uses seven rules and supports a wide range of possible use cases, ensuring compatibility and reproducibility of proteoform annotations. Standardizing proteoform sequences will simplify storage, comparison, and reanalysis of proteomic studies, and the Consortium welcomes input and contributions from the research community on the continued design and maintenance of this standard.

Cyclic Thiosulfinates and Cyclic Disulfides Selectively Cross-Link Thiols While Avoiding Modification of Lone Thiols.

This work addresses the need for chemical tools that can selectively form cross-links. Contemporary thiol-selective cross-linkers, for example, modify all accessible thiols, but only form cross-links between a subset. The resulting terminal "dead-end" modifications of lone thiols are toxic, confound cross-linking-based studies of macromolecular structure, and are an undesired, and currently unavoidable, byproduct in polymer synthesis. Using the thiol pair of Cu/Zn-superoxide dismutase (SOD1), we demonstrated that cyclic disulfides, including the drug/nutritional supplement lipoic acid, efficiently cross-linked thiol pairs but avoided dead-end modifications. Thiolate-directed nucleophilic attack upon the cyclic disulfide resulted in thiol-disulfide exchange and ring cleavage. The resulting disulfide-tethered terminal thiolate moiety either directed the reverse reaction, releasing the cyclic disulfide, or participated in oxidative disulfide (cross-link) formation. We hypothesized, and confirmed with density functional theory (DFT) calculations, that mono- S-oxo derivatives of cyclic disulfides formed a terminal sulfenic acid upon ring cleavage that obviated the previously rate-limiting step, thiol oxidation, and accelerated the new rate-determining step, ring cleavage. Our calculations suggest that the origin of accelerated ring cleavage is improved frontier molecular orbital overlap in the thiolate-disulfide interchange transition. Five- to seven-membered cyclic thiosulfinates were synthesized and efficiently cross-linked up to 104-fold faster than their cyclic disulfide precursors; functioned in the presence of biological concentrations of glutathione; and acted as cell-permeable, potent, tolerable, intracellular cross-linkers. This new class of thiol cross-linkers exhibited click-like attributes including, high yields driven by the enthalpies of disulfide and water formation, orthogonality with common functional groups, water-compatibility, and ring strain-dependence.

In Vitro Liquid Extraction Surface Analysis Mass Spectrometry (ivLESA-MS) for Direct Metabolic Analysis of Adherent Cells in Culture.

Conventional metabolomic methods include extensive sample preparation steps and long analytical run times, increasing the likelihood of processing artifacts and limiting high throughput applications. We present here in vitro liquid extraction surface analysis mass spectrometry (ivLESA-MS), a variation on LESA-MS, performed directly on adherent cells grown in 96-well cell culture plates. To accomplish this, culture medium was aspirated immediately prior to analysis, and metabolites were extracted using LESA from the cell monolayer surface, followed by nano-electrospray ionization and MS analysis in negative ion mode. We applied this platform to characterize and compare lipidomic profiles of multiple breast cancer cell lines growing in culture (MCF-7, ZR-75-1, MDA-MB-453, and MDA-MB-231) and revealed distinct and reproducible lipidomic signatures between the cell lines. Additionally, we demonstrated time-dependent processing artifacts, underscoring the importance of immediate analysis. ivLESA-MS represents a rapid in vitro metabolomic method, which precludes the need for quenching, cell harvesting, sample preparation, and chromatography, significantly shortening preparation and analysis time while minimizing processing artifacts. This method could be further adapted to test drugs in vitro in a high throughput manner.

Secretion, isotopic labeling and deglycosylation of N-acylethanolamine acid amidase for biophysical studies.

N-acylethanolamine acid amidase (NAAA) is an N-terminal nucleophile (Ntn) enzyme with a catalytic cysteine residue that has highest activity at acidic pH. The most prominent substrate hydrolyzed is palmitoylethanolamine (PEA), which regulates inflammation. Inhibitors of NAAA have been shown to increase endogenous levels of PEA, and are of interest as potential treatments for inflammatory disorders and other maladies. Currently, there are no X-ray or NMR structures of NAAA available to inform medicinal chemistry. Additionally, there are a limited number of enzyme structures available that are within the Ntn-hydrolase family, have a catalytic cysteine residue, and have a high sequence homology. For these reasons, we developed expression and purification methods for the production of enzyme samples amenable to structural characterization. Mammalian cells are necessary for post-translational processing, including signal sequence cleavage and glycosylation, that are required for a correctly folded zymogen before conversion to active, and mature enzyme. We have identified an expression construct, mammalian cell line, specific media and additives to express and secrete hNAAA zymogen and we further optimized propagation conditions and show this secretion method is suitable for isotopic labeling of the protein. We refined purification methods to achieve a high degree of protein purity potentially suited to crystallography. Glycosylated proteins can present challenges to biophysical methods. Therefore we deglycosylate the enzyme and show that the activity of the mature enzyme is not affected by deglycosylation.

Rapid discrimination of pediatric brain tumors by mass spectrometry imaging.

PURPOSE: Medulloblastoma, the most common primary pediatric malignant brain tumor, originates in the posterior fossa of the brain. Pineoblastoma, which originates within the pineal gland, is a rarer malignancy that also presents in the pediatric population. Medulloblastoma and pineoblastoma exhibit overlapping clinical features and have similar histopathological characteristics. Histopathological similarities confound rapid diagnoses of these two tumor types. We have conducted a pilot feasibility study analyzing the molecular profile of archived frozen human tumor specimens using mass spectrometry imaging (MSI) to identify potential biomarkers capable of classifying and distinguishing between medulloblastoma and pineoblastoma. METHODS: We performed matrix-assisted laser desorption ionization Fourier transform ion cyclotron resonance mass spectrometry imaging on eight medulloblastoma biopsy specimens and three pineoblastoma biopsy specimens. Multivariate statistical analyses were performed on the MSI dataset to generate classifiers that distinguish the two tumor types. Lastly, the molecules that were discriminative of tumor type were queried against the Lipid Maps database and identified. RESULTS: In this pilot study we show that medulloblastoma and pineoblastoma can be discriminated using molecular profiles determined by MSI. The highest-ranking discriminating classifiers of medulloblastoma and pineoblastoma were glycerophosphoglycerols and sphingolipids, respectively. CONCLUSION: We demonstrate proof-of-concept that medulloblastoma and pineoblastoma can be rapidly distinguished by using MSI lipid profiles. We identified biomarker candidates capable of distinguishing these two histopathologically similar tumor types. This work expands the current molecular knowledge of medulloblastoma and pineoblastoma by characterizing their lipidomic profiles, which may be useful for developing novel diagnostic, prognostic and therapeutic strategies.

Heavy Sugar and Heavy Water Create Tunable Intact Protein Mass Increases for Quantitative Mass Spectrometry in Any Feed and Organism.

Stable isotope labeling techniques for quantitative top-down proteomics face unique challenges. These include unpredictable mass shifts following isotope labeling, which impedes analysis of unknown proteins and complex mixtures and exponentially greater susceptibility to incomplete isotope incorporation, manifesting as broadening of labeled intact protein peaks. Like popular bottom-up isotope labeling techniques, most top-down labeling methods are restricted to defined media/feed as well as amino acid auxotrophic organisms. We present a labeling method optimized for top-down proteomics that overcomes these challenges. We demonstrated this method through the spiking of 13C-sugar or 2H-water into standard laboratory feedstocks, resulting in tunable intact protein mass increases (TIPMI). After mixing of labeled and unlabeled samples, direct comparison of light and heavy peaks allowed for the relative quantitation of intact proteins in three popular model organisms, including prokaryotic and eukaryotic microorganisms and an animal. This internal standard method proved to be more accurate than label-free quantitation in our hands. Advantages over top-down SILAC include working equally well in nutrient-rich media, conceivably expanding applicability to any organism and all classes of biomolecules, not requiring high-resolving power MS for quantitation and being relatively inexpensive.

The central nervous system transcriptome of the weakly electric brown ghost knifefish (Apteronotus leptorhynchus): de novo assembly, annotation, and proteomics validation.

BACKGROUND: The brown ghost knifefish (Apteronotus leptorhynchus) is a weakly electric teleost fish of particular interest as a versatile model system for a variety of research areas in neuroscience and biology. The comprehensive information available on the neurophysiology and neuroanatomy of this organism has enabled significant advances in such areas as the study of the neural basis of behavior, the development of adult-born neurons in the central nervous system and their involvement in the regeneration of nervous tissue, as well as brain aging and senescence. Despite substantial scientific interest in this species, no genomic resources are currently available. RESULTS: Here, we report the de novo assembly and annotation of the A. leptorhynchus transcriptome. After evaluating several trimming and transcript reconstruction strategies, de novo assembly using Trinity uncovered 42,459 unique contigs containing at least a partial protein-coding sequence based on alignment to a reference set of known Actinopterygii sequences. As many as 11,847 of these contigs contained full or near-full length protein sequences, providing broad coverage of the proteome. A variety of non-coding RNA sequences were also identified and annotated, including conserved long intergenic non-coding RNA and other long non-coding RNA observed previously to be expressed in adult zebrafish (Danio rerio) brain, as well as a variety of miRNA, snRNA, and snoRNA. Shotgun proteomics confirmed translation of open reading frames from over 2,000 transcripts, including alternative splice variants. Assignment of tandem mass spectra was greatly improved by use of the assembly compared to databases of sequences from closely related organisms. The assembly and raw reads have been deposited at DDBJ/EMBL/GenBank under the accession number GBKR00000000. Tandem mass spectrometry data is available via ProteomeXchange with identifier PXD001285. CONCLUSIONS: Presented here is the first release of an annotated de novo transcriptome assembly from Apteronotus leptorhynchus, providing a broad overview of RNA expressed in central nervous system tissue. The assembly, which includes substantial coverage of a wide variety of both protein coding and non-coding transcripts, will allow the development of better tools to understand the mechanisms underlying unique characteristics of the knifefish model system, such as their tremendous regenerative capacity and negligible brain senescence.

Artifacts to avoid while taking advantage of top-down mass spectrometry based detection of protein S-thiolation.

Bottom-up MS studies typically employ a reduction and alkylation step that eliminates a class of PTM, S-thiolation. Given that molecular oxygen can mediate S-thiolation from reduced thiols, which are abundant in the reducing intracellular milieu, we investigated the possibility that some S-thiolation modifications are artifacts of protein preparation. Cu/Zn-superoxide dismutase (SOD1) was chosen for this case study as it has a reactive surface cysteine residue, which is readily cysteinylated in vitro. The ability of oxygen to generate S-thiolation artifacts was tested by comparing purification of SOD1 from postmortem human cerebral cortex under aerobic and anaerobic conditions. S-thiolation was ∼50% higher in aerobically processed preparations, consistent with oxygen-dependent artifactual S-thiolation. The ability of endogenous small molecule disulfides (e.g. cystine) to participate in artifactual S-thiolation was tested by blocking reactive protein cysteine residues during anaerobic homogenization. A 50-fold reduction in S-thiolation occurred indicating that the majority of S-thiolation observed aerobically was artifact. Tissue-specific artifacts were explored by comparing brain- and blood-derived protein, with remarkably more artifacts observed in brain-derived SOD1. Given the potential for such artifacts, rules of thumb for sample preparation are provided. This study demonstrates that without taking extraordinary precaution, artifactual S-thiolation of highly reactive, surface-exposed, cysteine residues can result.

QUDeX-MS: hydrogen/deuterium exchange calculation for mass spectra with resolved isotopic fine structure.

BACKGROUND: Hydrogen/deuterium exchange (HDX) coupled to mass spectrometry permits analysis of structure, dynamics, and molecular interactions of proteins. HDX mass spectrometry is confounded by deuterium exchange-associated peaks overlapping with peaks of heavy, natural abundance isotopes, such as carbon-13. Recent studies demonstrated that high-performance mass spectrometers could resolve isotopic fine structure and eliminate this peak overlap, allowing direct detection and quantification of deuterium incorporation. RESULTS: Here, we present a graphical tool that allows for a rapid and automated estimation of deuterium incorporation from a spectrum with isotopic fine structure. Given a peptide sequence (or elemental formula) and charge state, the mass-to-charge ratios of deuterium-associated peaks of the specified ion is determined. Intensities of peaks in an experimental mass spectrum within bins corresponding to these values are used to determine the distribution of deuterium incorporated. A theoretical spectrum can then be calculated based on the estimated distribution of deuterium exchange to confirm interpretation of the spectrum. Deuterium incorporation can also be detected for ion signals without a priori specification of an elemental formula, permitting detection of exchange in complex samples of unidentified material such as natural organic matter. A tool is also incorporated into QUDeX-MS to help in assigning ion signals from peptides arising from enzymatic digestion of proteins. MATLAB-deployable and standalone versions are available for academic use at qudex-ms.sourceforge.net and agarlabs.com . CONCLUSION: Isotopic fine structure HDX-MS offers the potential to increase sequence coverage of proteins being analyzed through mass accuracy and deconvolution of overlapping ion signals. As previously demonstrated, however, the data analysis workflow for HDX-MS data with resolved isotopic fine structure is distinct. QUDeX-MS we hope will aid in the adoption of isotopic fine structure HDX-MS by providing an intuitive workflow and interface for data analysis.