De novo glycan sequencing by electronic excitation dissociation MS2-guided MS3 analysis on an Omnitrap-Orbitrap hybrid instrument.

Comprehensive de novo glycan sequencing remains an elusive goal due to the structural diversity and complexity of glycans. Present strategies employing collision-induced dissociation (CID) and higher energy collisional dissociation (HCD)-based multi-stage tandem mass spectrometry (MSn) or MS/MS combined with sequential exoglycosidase digestions are inherently low-throughput and difficult to automate. Compared to CID and HCD, electron transfer dissociation (ETD) and electron capture dissociation (ECD) each generate more cross-ring cleavages informative about linkage positions, but electronic excitation dissociation (EED) exceeds the information content of all other methods and is also applicable to analysis of singly charged precursors. Although EED can provide extensive glycan structural information in a single stage of MS/MS, its performance has largely been limited to FTICR MS, and thus it has not been widely adopted by the glycoscience research community. Here, the effective performance of EED MS/MS was demonstrated on a hybrid Orbitrap-Omnitrap QE-HF instrument, with high sensitivity, fragmentation efficiency, and analysis speed. In addition, a novel EED MS2-guided MS3 approach was developed for detailed glycan structural analysis. Automated topology reconstruction from MS2 and MS3 spectra could be achieved with a modified GlycoDeNovo software. We showed that the topology and linkage configurations of the Man9GlcNAc2 glycan can be accurately determined from first principles based on one EED MS2 and two CID-EED MS3 analyses, without reliance on biological knowledge, a structure database or a spectral library. The presented approach holds great promise for autonomous, comprehensive and de novo glycan sequencing.

Proteomics Standards Initiative's ProForma 2.0: Unifying the Encoding of Proteoforms and Peptidoforms.

It is important for the proteomics community to have a standardized manner to represent all possible variations of a protein or peptide primary sequence, including natural, chemically induced, and artifactual modifications. The Human Proteome Organization Proteomics Standards Initiative in collaboration with several members of the Consortium for Top-Down Proteomics (CTDP) has developed a standard notation called ProForma 2.0, which is a substantial extension of the original ProForma notation developed by the CTDP. ProForma 2.0 aims to unify the representation of proteoforms and peptidoforms. ProForma 2.0 supports use cases needed for bottom-up and middle-/top-down proteomics approaches and allows the encoding of highly modified proteins and peptides using a human- and machine-readable string. ProForma 2.0 can be used to represent protein modifications in a specified or ambiguous location, designated by mass shifts, chemical formulas, or controlled vocabulary terms, including cross-links (natural and chemical) and atomic isotopes. Notational conventions are based on public controlled vocabularies and ontologies. The most up-to-date full specification document and information about software implementations are available at http://psidev.info/proforma.

Data-independent acquisition mass spectrometry for site-specific glycoproteomics characterization of SARS-CoV-2 spike protein.

The spike protein of SARS-CoV-2, the virus responsible for the global pandemic of COVID-19, is an abundant, heavily glycosylated surface protein that plays a key role in receptor binding and host cell fusion, and is the focus of all current vaccine development efforts. Variants of concern are now circulating worldwide that exhibit mutations in the spike protein. Protein sequence and glycosylation variations of the spike may affect viral fitness, antigenicity, and immune evasion. Global surveillance of the virus currently involves genome sequencing, but tracking emerging variants should include quantitative measurement of changes in site-specific glycosylation as well. In this work, we used data-dependent acquisition (DDA) and data-independent acquisition (DIA) mass spectrometry to quantitatively characterize the five N-linked glycosylation sites of the glycoprotein standard alpha-1-acid glycoprotein (AGP), as well as the 22 sites of the SARS-CoV-2 spike protein. We found that DIA compared favorably to DDA in sensitivity, resulting in more assignments of low-abundance glycopeptides. However, the reproducibility across replicates of DIA-identified glycopeptides was lower than that of DDA, possibly due to the difficulty of reliably assigning low-abundance glycopeptides confidently. The differences in the data acquired between the two methods suggest that DIA outperforms DDA in terms of glycoprotein coverage but that overall performance is a balance of sensitivity, selectivity, and statistical confidence in glycoproteomics. We assert that these analytical and bioinformatics methods for assigning and quantifying glycoforms would benefit the process of tracking viral variants as well as for vaccine development.

Effect of supersaturated oxygen emulsion treatment on chloropicrin-induced chemical injury in ex vivo rabbit cornea.

With a possibility for the use of chemical weapons in battlefield or in terrorist activities, effective therapies against the devastating ocular injuries, from their exposure, are needed. Oxygen plays a vital role in ocular tissue preservation and wound repair. We tested the efficacy of supersaturated oxygen emulsion (SSOE) in reducing ex vivo corneal and keratocyte injury from chloropicrin (CP). CP, currently used as a pesticide, is a chemical threat agent like the vesicating mustard agents and causes severe corneal injury. Since our previous study in human corneal epithelial cells showed the treatment potential of SSOE (55 %), we further tested its efficacy in an ex vivo CP-induced rabbit corneal injury model. Corneas were exposed to CP (700 nmol) for 2 h, washed and cultured with or without SSOE for 24 h or 96 h. At 96 h post CP exposure, SSOE treatment presented a healing tendency of the corneal epithelial layer, and abrogated the CP-induced epithelial apoptotic cell death. SSOE treatment also reduced the CP induced DNA damage (H2A.X phosphorylation) and inflammatory markers (e.g. MMP9, IL-21, MIP-1ß, TNFα). Further examination of the treatment efficacy of SSOE alone or in combination with other therapies in in vivo cornea injury models for CP and vesicants, is warranted.

GAGrank: Software for Glycosaminoglycan Sequence Ranking Using a Bipartite Graph Model.

The sulfated glycosaminoglycans (GAGs) are long, linear polysaccharide chains that are typically found as the glycan portion of proteoglycans. These GAGs are characterized by repeating disaccharide units with variable sulfation and acetylation patterns along the chain. GAG length and modification patterns have profound impacts on growth factor signaling mechanisms central to numerous physiological processes. Electron activated dissociation tandem mass spectrometry is a very effective technique for assigning the structures of GAG saccharides; however, manual interpretation of the resulting complex tandem mass spectra is a difficult and time-consuming process that drives the development of computational methods for accurate and efficient sequencing. We have recently published GAGfinder, the first peak picking and elemental composition assignment algorithm specifically designed for GAG tandem mass spectra. Here, we present GAGrank, a novel network-based method for determining GAG structure using information extracted from tandem mass spectra using GAGfinder. GAGrank is based on Google's PageRank algorithm for ranking websites for search engine output. In particular, it is an implementation of BiRank, an extension of PageRank for bipartite networks. In our implementation, the two partitions comprise every possible sequence for a given GAG composition and the tandem MS fragments found using GAGfinder. Sequences are given a higher ranking if they link to many important fragments. Using the simulated annealing probabilistic optimization technique, we optimized GAGrank's parameters on ten training sequences. We then validated GAGrank's performance on three validation sequences. We also demonstrated GAGrank's ability to sequence isomeric mixtures using two mixtures at five different ratios.

Phosgene oxime: a highly toxic urticant and emerging chemical threat.

Highly toxic industrial chemicals that are widely accessible, and hazardous chemicals like phosgene oxime (CX) that can be easily synthesized, pose a serious threat as potential chemical weapons. In addition, their accidental release can lead to chemical emergencies and mass casualties. CX, an urticant, or nettle agent, grouped with vesicating agents, causes instant pain, injury and systemic effects, which can lead to mortality. With faster cutaneous penetration, corrosive properties, and more potent toxicity compared to other vesicating agents, CX causes instantaneous and severe tissue damage. CX, a potential chemical terrorism threat agent, could therefore be weaponized with other chemical warfare agents to enhance their harmful effects. CX is the least studied vesicant and its acute and long-term toxic effects as well as its mechanism of action are largely unknown. This has hampered the identification of therapeutic targets and the development of effective medical countermeasures. There are only protective measures, decontamination, and supportive treatments available for reducing the toxic effects from CX exposure. This review summarizes CX toxicity, its known mechanism of action, and our current studies exploring the role of mast cell activation and associated signaling pathways in CX cutaneous exposure under the National Institutes of Health Countermeasures Against Chemical Threats program. Potential treatment options and the development of effective targeted countermeasures against CX-induced morbidity and mortality is also discussed.

A Perspective on the Confident Comparison of Glycoprotein Site-Specific Glycosylation in Sample Cohorts.

Protein glycosylation, resulting from glycosyl transferase reactions under complex control in the secretory pathway, consists of a distribution of related glycoforms at each glycosylation site. Because the biosynthetic substrate concentration and transport rates depend on architecture and other aspects of cellular phenotypes, site-specific glycosylation cannot be predicted accurately from genomic, transcriptomic, or proteomic information. Rather, it is necessary to quantify glycosylation at each protein site and how this changes among a sample cohort to provide information about disease mechanisms. At present, mature mass spectrometry-based methods allow for qualitative assignment of the glycan composition and glycosylation site of singly glycosylated proteolytic peptides. To make such quantitative comparisons, it is necessary to sample the glycosylation distribution with sufficient coverage and accuracy for confident assessment of the glycosylation changes that occur in the biological cohort. In this Perspective, we discuss the unmet needs for mass spectrometry acquisition methods and bioinformatics for the confident comparison of protein site-specific glycosylation among sample cohorts.

Proteomics, Glycomics, and Glycoproteomics of Matrisome Molecules.

The most straightforward applications of proteomics database searching involve intracellular proteins. Although intracellular gene products number in the thousands, their well-defined post-translational modifications (PTMs) makes database searching practical. By contrast, cell surface and extracellular matrisome proteins pass through the secretory pathway where many become glycosylated, modulating their physicochemical properties, adhesive interactions, and diversifying their functions. Although matrisome proteins number only a few hundred, their high degree of complex glycosylation multiplies the number of theoretical proteoforms by orders of magnitude. Given that extracellular networks that mediate cell-cell and cell-pathogen interactions in physiology depend on glycosylation, it is important to characterize the proteomes, glycomes, and glycoproteomes of matrisome molecules that exist in a given biological context. In this review, we summarize proteomics approaches for characterizing matrisome molecules, with an emphasis on applications to brain diseases. We demonstrate the availability of methods that should greatly increase the availability of information on matrisome molecular structure associated with health and disease.

Pyteomics 4.0: Five Years of Development of a Python Proteomics Framework.

Many of the novel ideas that drive today's proteomic technologies are focused essentially on experimental or data-processing workflows. The latter are implemented and published in a number of ways, from custom scripts and programs, to projects built using general-purpose or specialized workflow engines; a large part of routine data processing is performed manually or with custom scripts that remain unpublished. Facilitating the development of reproducible data-processing workflows becomes essential for increasing the efficiency of proteomic research. To assist in overcoming the bioinformatics challenges in the daily practice of proteomic laboratories, 5 years ago we developed and announced Pyteomics, a freely available open-source library providing Python interfaces to proteomic data. We summarize the new functionality of Pyteomics developed during the time since its introduction.

Glycomic and Proteomic Changes in Aging Brain Nigrostriatal Pathway.

Parkinson's disease (PD) is a neurological disorder characterized by the progressive loss of functional dopaminergic neurons in the nigrostriatal pathway in the brain. Although current treatments provide only symptomatic relief, gene therapy has the potential to slow or halt the degeneration of nigrostriatal dopamine neurons in PD patients. Adeno-associated viruses (AAV) are vectors of choice in gene therapy because of their well-characterized safety and efficacy profiles; however, although gene therapy has been successful in preclinical models of the disease, clinical trials in humans have failed to demonstrate efficacy. Significantly, all primary AAV receptors of the virus are glycans. We thus hypothesize that age related changes in glycan receptors of heparan sulfate (HS) proteoglycans (receptor for rAAV2), and/or N-glycans with terminal galactose (receptor for rAAV9) results in poor adeno-associated virus binding in either the striatum or substantia nigra, or both, affecting transduction and gene delivery. To test our hypothesis we analyzed the striatum and substantia nigra for changes in HS, N-glycans and proteomic signatures in young versus aged rat brain striatum and substantia nigra. We observed different brain region-specific HS disaccharide profiles in aged compared with young adult rats for brain region-specific profiles in striatum versus substantia nigra. We observed brain region- and age-specific N-glycan compositional profiles with respect to the terminal galactose units that serve as receptors for AAV9. We also observed brain region-specific changes in protein expression in the aging nigrostriatal pathway. These studies provide insight into age- and brain region-specific changes in glycan receptors and proteome that will inform design of improved viral vectors for Parkinson Disease (PD) gene therapy.

Deep Sequencing of Complex Proteoglycans: A Novel Strategy for High Coverage and Site-specific Identification of Glycosaminoglycan-linked Peptides.

Proteoglycans are distributed in all animal tissues and play critical, multifaceted, physiological roles. Expressed in a spatially and temporally regulated manner, these molecules regulate interactions among growth factors and cell surface receptors and play key roles in basement membranes and other extracellular matrices. Because of the high degree of glycosylation by glycosaminoglycan (GAG), N-glycan and mucin-type O-glycan classes, the peptide sequence coverage of complex proteoglycans is revealed poorly by standard mass spectrometry-based proteomics methods. As a result, there is little information concerning how proteoglycan site specific glycosylation changes during normal and pathological processes. Here, we developed a workflow to improve sequence coverage and identification of glycosylated peptides in proteoglycans. We applied this workflow to the small leucine-rich proteoglycan decorin and three hyalectan proteoglycans: neurocan, brevican, and aggrecan.We characterized glycosylation of these proteoglycans using LC-MS methods easily implemented on instruments widely used in proteomics laboratories. For decorin, we assigned the linker-glycosite and three N-glycosylation sites. For neurocan and brevican, we identified densely glycosylated mucin-like regions in the extended domains. For aggrecan, we identified 50 linker-glycosites and mucin-type O-glycosites in the extended region and N-glycosites in the globular domains, many of which are novel and have not been observed previously. Most importantly, we demonstrate an LC-MS and bioinformatics approach that will enable routine analysis of proteoglycan glycosylation from biological samples to assess their role in pathophysiology.

Software for Peak Finding and Elemental Composition Assignment for Glycosaminoglycan Tandem Mass Spectra.

Glycosaminoglycans (GAGs) covalently linked to proteoglycans (PGs) are characterized by repeating disaccharide units and variable sulfation patterns along the chain. GAG length and sulfation patterns impact disease etiology, cellular signaling, and structural support for cells. We and others have demonstrated the usefulness of tandem mass spectrometry (MS2) for assigning the structures of GAG saccharides; however, manual interpretation of tandem mass spectra is time-consuming, so computational methods must be employed. In the proteomics domain, the identification of monoisotopic peaks and charge states relies on algorithms that use averagine, or the average building block of the compound class being analyzed. Although these methods perform well for protein and peptide spectra, they perform poorly on GAG tandem mass spectra, because a single average building block does not characterize the variable sulfation of GAG disaccharide units. In addition, it is necessary to assign product ion isotope patterns to interpret the tandem mass spectra of GAG saccharides. To address these problems, we developed GAGfinder, the first tandem mass spectrum peak finding algorithm developed specifically for GAGs. We define peak finding as assigning experimental isotopic peaks directly to a given product ion composition, as opposed to deconvolution or peak picking, which are terms more accurately describing the existing methods previously mentioned. GAGfinder is a targeted, brute force approach to spectrum analysis that uses precursor composition information to generate all theoretical fragments. GAGfinder also performs peak isotope composition annotation, which is typically a subsequent step for averagine-based methods. Data are available via ProteomeXchange with identifier PXD009101.

Comparison of Collisional and Electron-Based Dissociation Modes for Middle-Down Analysis of Multiply Glycosylated Peptides.

Analysis of singly glycosylated peptides has evolved to a point where large-scale LC-MS analyses can be performed at almost the same scale as proteomics experiments. While collisionally activated dissociation (CAD) remains the mainstay of bottom-up analyses, it performs poorly for the middle-down analysis of multiply glycosylated peptides. With improvements in instrumentation, electron-activated dissociation (ExD) modes are becoming increasingly prevalent for proteomics experiments and for the analysis of fragile modifications such as glycosylation. While these methods have been applied for glycopeptide analysis in isolated studies, an organized effort to compare their efficiencies, particularly for analysis of multiply glycosylated peptides (termed here middle-down glycoproteomics), has not been made. We therefore compared the performance of different ExD modes for middle-down glycopeptide analyses. We identified key features among the different dissociation modes and show that increased electron energy and supplemental activation provide the most useful data for middle-down glycopeptide analysis. Graphical Abstract.

Cryptosporidium parvum vaccine candidates are incompletely modified with O-linked-N-acetylgalactosamine or contain N-terminal N-myristate and S-palmitate.

Cryptosporidium parvum (studied here) and Cryptosporidium hominis are important causes of diarrhea in infants and immunosuppressed persons. C. parvum vaccine candidates, which are on the surface of sporozoites, include glycoproteins with Ser- and Thr-rich domains (Gp15, Gp40, and Gp900) and a low complexity, acidic protein (Cp23). Here we used mass spectrometry to determine that O-linked GalNAc is present in dense arrays on a glycopeptide with consecutive Ser derived from Gp40 and on glycopeptides with consecutive Thr derived from Gp20, a novel C. parvum glycoprotein with a formula weight of ~20 kDa. In contrast, the occupied Ser or Thr residues in glycopeptides from Gp15 and Gp900 are isolated from one another. Gly at the N-terminus of Cp23 is N-myristoylated, while Cys, the second amino acid, is S-palmitoylated. In summary, C. parvum O-GalNAc transferases, which are homologs of host enzymes, densely modify arrays of Ser or Thr, as well as isolated Ser and Thr residues on C. parvum vaccine candidates. The N-terminus of an immunodominant antigen has lipid modifications similar to those of host cells and other apicomplexan parasites. Mass spectrometric demonstration here of glycopeptides with O-glycans complements previous identification C. parvum O-GalNAc transferases, lectin binding to vaccine candidates, and human and mouse antibodies binding to glycopeptides. The significance of these post-translational modifications is discussed with regards to the function of these proteins and the design of serological tests and vaccines.

Microfluidic Capillary Electrophoresis-Mass Spectrometry for Analysis of Monosaccharides, Oligosaccharides, and Glycopeptides.

Glycomics and glycoproteomics analyses by mass spectrometry require efficient front-end separation methods to enable deep characterization of heterogeneous glycoform populations. Chromatography methods are generally limited in their ability to resolve glycoforms using mobile phases that are compatible with online liquid chromatography-mass spectrometry (LC-MS). The adoption of capillary electrophoresis-mass spectrometry methods (CE-MS) for glycomics and glycoproteomics is limited by the lack of convenient interfaces for coupling the CE devices to mass spectrometers. Here, we describe the application of a microfluidics-based CE-MS system for analysis of released glycans, glycopeptides and monosaccharides. We demonstrate a single CE method for three different modalities, thus contributing to comprehensive glycoproteomics analyses. In addition, we explored compatible sample derivatization methods. We used glycan TMT-labeling to improve electrophoretic migration and enable multiplexed quantitation by tandem MS. We used sialic acid linkage-specific derivatization methods to improve separation and the level of information obtained from a single analytical step. Capillary electrophoresis greatly improved glycoform separation for both released glycans and glycopeptides over that reported for chromatography modes more frequently employed for such analyses. Overall, the CE-MS method described here enables rapid setup and analysis of glycans and glycopeptides using mass spectrometry.

Use of an informed search space maximizes confidence of site-specific assignment of glycoprotein glycosylation.

In order to interpret glycopeptide tandem mass spectra, it is necessary to estimate the theoretical glycan compositions and peptide sequences, known as the search space. The simplest way to do this is to build a naïve search space from sets of glycan compositions from public databases and to assume that the target glycoprotein is pure. Often, however, purified glycoproteins contain co-purified glycoprotein contaminants that have the potential to confound assignment of tandem mass spectra based on naïve assumptions. In addition, there is increasing need to characterize glycopeptides from complex biological mixtures. Fortunately, liquid chromatography-mass spectrometry (LC-MS) methods for glycomics and proteomics are now mature and accessible. We demonstrate the value of using an informed search space built from measured glycomes and proteomes to define the search space for interpretation of glycoproteomics data. We show this using α-1-acid glycoprotein (AGP) mixed into a set of increasingly complex matrices. As the mixture complexity increases, the naïve search space balloons and the ability to assign glycopeptides with acceptable confidence diminishes. In addition, it is not possible to identify glycopeptides not foreseen as part of the naïve search space. A search space built from released glycan glycomics and proteomics data is smaller than its naïve counterpart while including the full range of proteins detected in the mixture. This maximizes the ability to assign glycopeptide tandem mass spectra with confidence. As the mixture complexity increases, the number of tandem mass spectra per glycopeptide precursor ion decreases, resulting in lower overall scores and reduced depth of coverage for the target glycoprotein. We suggest use of α-1-acid glycoprotein as a standard to gauge effectiveness of analytical methods and bioinformatics search parameters for glycoproteomics studies. Graphical Abstract Assignment of site specific glycosylation from LC-tandemMS data.

Integrated Omics and Computational Glycobiology Reveal Structural Basis for Influenza A Virus Glycan Microheterogeneity and Host Interactions.

Despite sustained biomedical research effort, influenza A virus remains an imminent threat to the world population and a major healthcare burden. The challenge in developing vaccines against influenza is the ability of the virus to mutate rapidly in response to selective immune pressure. Hemagglutinin is the predominant surface glycoprotein and the primary determinant of antigenicity, virulence and zoonotic potential. Mutations leading to changes in the number of HA glycosylation sites are often reported. Such genetic sequencing studies predict at best the disruption or creation of sequons for N-linked glycosylation; they do not reflect actual phenotypic changes in HA structure. Therefore, combined analysis of glycan micro and macro-heterogeneity and bioassays will better define the relationships among glycosylation, viral bioactivity and evolution. We present a study that integrates proteomics, glycomics and glycoproteomics of HA before and after adaptation to innate immune system pressure. We combined this information with glycan array and immune lectin binding data to correlate the phenotypic changes with biological activity. Underprocessed glycoforms predominated at the glycosylation sites found to be involved in viral evolution in response to selection pressures and interactions with innate immune-lectins. To understand the structural basis for site-specific glycan microheterogeneity at these sites, we performed structural modeling and molecular dynamics simulations. We observed that the presence of immature, high-mannose type glycans at a particular site correlated with reduced accessibility to glycan remodeling enzymes. Further, the high mannose glycans at sites implicated in immune lectin recognition were predicted to be capable of forming trimeric interactions with the immune-lectin surfactant protein-D.

Comparative lipid profiling of the cnidarian Aiptasia pallida and its dinoflagellate symbiont.

Corals and other cnidarians house photosynthetic dinoflagellate symbionts within membrane-bound compartments inside gastrodermal cells. Nutritional interchanges between the partners produce carbohydrates and lipids for metabolism, growth, energy stores, and cellular structures. Although lipids play a central role in the both the energetics and the structural/morphological features of the symbiosis, previous research has primarily focused on the fatty acid and neutral lipid composition of the host and symbiont. In this study we conducted a mass spectrometry-based survey of the lipidomic changes associated with symbiosis in the sea anemone Aiptasia pallida, an important model system for coral symbiosis. Lipid extracts from A. pallida in and out of symbiosis with its symbiont Symbiodinium were prepared and analyzed using negative-ion electrospray ionization quadrupole time-of-flight mass spectrometry. Through this analysis we have identified, by exact mass and collision-induced dissociation mass spectrometry (MS/MS), several classes of glycerophospholipids in A. pallida. Several molecular species of di-acyl phosphatidylinositol and phosphatidylserine as well as 1-alkyl, 2-acyl phosphatidylethanolamine (PE) and phosphatidycholine were identified. The 1-alkyl, 2-acyl PEs are acid sensitive suggestive that they are plasmalogen PEs possessing a double bond at the 1-position of the alkyl linked chain. In addition, we identified several molecular species of phosphonosphingolipids called ceramide aminoethylphosphonates in anemone lipid extracts by the release of a characteristic negative product ion at m/z 124.014 during MS/MS analysis. Sulfoquinovosyldiacylglycerol (SQDG), an anionic lipid often found in photosynthetic organisms, was identified as a prominent component of Symbiodinium lipid extracts. A comparison of anemone lipid profiles revealed a subset of lipids that show dramatic differences in abundance when anemones are in the symbiotic state as compared to the non-symbiotic state. The data generated in this analysis will serve as a resource to further investigate the role of lipids in symbiosis between Symbiodinium and A. pallida.