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Cerebral venous thrombosis is characterized by infarction with focal neurologic deficits and increased intracranial pressure. As a very rare complication of some vaccines against Covid-19, the disorder is accompanied by disseminated intravascular coagulation and hemorrhage.

  [...]the extent and mode of protection are still under debate [2]. [...]a vaccine that effectively stimulates complete protective immunity by the cellular branch (cytotoxic T lymphocytes) and/or the humoral branch (antibodies) of the immune system has yet to emerge. An alternative approach, as others have proposed [56], [57], may lie in eliciting anti-carbohydrate antibodies, as the high density of glycans on each gp120 monomer should enable efficient bivalent binding to individual envelope spikes. [...]new immunogens designed to elicit antibodies capable of intra-spike cross-linking--either carbohydrate epitopes within or between spike monomers, or protein epitopes between spike monomers--may prove critical to the induction of a broadly cross-reactive neutralizing antibody response.

Accurate glycopeptide identification in mass spectrometry-based glycoproteomics is a challenging problem at scale. Recent innovation has been made in increasing the scope and accuracy of glycopeptide identifications, with more precise uncertainty estimates for each part of the structure. We present a dynamically adapting relative retention time model for detecting and correcting ambiguous glycan assignments that are difficult to detect from fragmentation alone, a layered approach to glycopeptide fragmentation modeling that improves N -glycopeptide identification in samples without compromising identification quality, and a site-specific method to increase the depth of the glycoproteome confidently identifiable even further. We demonstrate our techniques on a set of previously published datasets, showing the performance gains at each stage of optimization. These techniques are provided in the open-source glycomics and glycoproteomics platform GlycReSoft available at https://github.com/mobiusklein/glycresoft . Glycopeptide identification by mass spectrometry is a complex problem. Here, the authors introduce a retention time model to resolve adduction, fragmentation models to improve identification rates, and glycosite-specific biosynthesis models to identify more spectra at the same confidence level.

Combined Degeneration from Nitrous Oxide UseA 32-year-old man with daily nitrous oxide inhalant use presented with an inability to walk. MRI of the whole spine revealed hyperintensities in the posterior spinal cord on T2-weighted images.

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.

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

ObjectivesData from the Centers for Disease Control and Prevention (CDC) show that firearm deaths are increasing in the USA. The aims of this study were to determine the magnitude of potential years of life lost due to firearms and to examine the evolution of firearm deaths on the basis of sex, race, and geographical location within the USA.MethodsData was extracted (2009–2018) from the National Vital Statistics Reports from the CDC and the Web-based Injury Statistics Query and Reporting System database. Years of potential life lost was calculated by the CDC standard of subtracting the age at death from the standard year of 80, and then summing the individual years of potential life lost (YPLL) across each cause of death.ResultsThe YPLL in 2017 and 2018 was higher for firearms than motor vehicle crashes (MVCs). In 2018, the YPLL for firearms was 1.42 million and 1.34 million for MVC. Males comprised the majority (85.4%) of the 38 929 firearm deaths. White males had the most YPLL due to suicide, with 4.95 million YPLL during the course of the 10-year period; black males had the most YPLL due to homicide with 3.2 million YPLL during the same time period. The largest number of suicides by firearms was in older white males. Firearm-related injury deaths were highest in the South, followed by the West, Midwest, and Northeast, respectively.ConclusionFirearms are now the leading cause of YPLL in trauma. Firearm deaths have overtaken MVC as the mechanism for the main cause of potential years of life lost since 2017. Suicide in white males accounts for more YPLL than homicides. Deaths related to firearms are potentially preventable causes of death and prevention efforts should be redirected.Level of evidenceLevel III—Descriptive Study.

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.

Despite the publication of several software tools for analysis of glycopeptide tandem mass spectra, there remains a lack of consensus regarding the most effective and appropriate methods. In part, this reflects problems with applying standard methods for proteomics database searching and false discovery rate calculation. While the analysis of small post-translational modifications (PTMs) may be regarded as an extension of proteomics database searching, glycosylation requires specialized approaches. This is because glycans are large and heterogeneous by nature, causing glycopeptides to exist as multiple glycosylated variants. Thus, the mass of the peptide cannot be calculated directly from that of the intact glycopeptide. In addition, the chemical nature of the glycan strongly influences product ion patterns observed for glycopeptides. As a result, glycopeptidomics requires specialized bioinformatics methods. We summarize the recent progress towards a consensus for effective glycopeptide tandem mass spectrometric analysis.

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.