Focal clusters of peri-synaptic matrix contribute to activity-dependent plasticity and memory in mice

Recent findings show that effective integration of novel information in the brain requires coordinated processes of homo- and heterosynaptic plasticity. In this work, we hypothesize that activity-dependent remodeling of the peri-synaptic extracellular matrix (ECM) contributes to these processes. We show that clusters of the peri-synaptic ECM, recognized by CS56 antibody, emerge in response to sensory stimuli, showing temporal and spatial coincidence with dendritic spine plasticity. Using CS56 co-immunoprecipitation of synaptosomal proteins, we identify several molecules involved in Ca2+ signaling, vesicle cycling, and AMPA-receptor exocytosis, thus suggesting a role in long-term potentiation (LTP). Finally, we show that, in the CA1 hippocampal region, the attenuation of CS56 glycoepitopes, through the depletion of versican as one of its main carriers, impairs LTP and object location memory in mice. These findings show that activity-dependent remodeling of the peri-synaptic ECM regulates the induction and consolidation of LTP, contributing to hippocampal-dependent memory.

A critical evaluation of ultrasensitive single-cell proteomics strategies

Success of mass spectrometry characterization of the proteome of single cells allows us to gain a greater understanding than afforded by transcriptomics alone but requires clear understanding of the tradeoffs between analytical throughput and precision. Recent advances in mass spectrometry acquisition techniques, including updated instrumentation and sample preparation, have improved the quality of peptide signals obtained from single cell data. However, much of the proteome remains uncharacterized, and higher throughput techniques often come at the expense of reduced sensitivity and coverage, which diminish the ability to measure proteoform heterogeneity, including splice variants and post-translational modifications, in single cell data analysis. Here, we assess the growing body of ultrasensitive single-cell approaches and their tradeoffs as researchers try to balance throughput and precision in their experiments.

Akt may associate with insulin-responsive vesicles via interaction with sortilin

Insulin-responsive vesicles (IRVs) deliver the glucose transporter Glut4 to the plasma membrane in response to activation of the insulin signaling cascade: insulin receptor-IRS-PI3 kinase-Akt-TBC1D4-Rab10. Previous studies have shown that Akt, TBC1D4, and Rab10 are compartmentalized on the IRVs. Although functionally significant, the mechanism of Akt association with the IRVs remains unknown. Using pull-down assays, immunofluorescence microscopy, and cross-linking, we have found that Akt may be recruited to the IRVs via the interaction with the juxtamembrane domain of the cytoplasmic C terminus of sortilin, a major IRV protein. Overexpression of full-length sortilin increases insulin-stimulated phosphorylation of TBC1D4 and glucose uptake in adipocytes, while overexpression of the cytoplasmic tail of sortilin has the opposite effect. Our findings demonstrate that the IRVs represent both a scaffold and a target of insulin signaling.

RAMZIS: a bioinformatic toolkit for rigorous assessment of the alterations to glycoprotein composition that occur during biological processes

Motivation

Glycosylation elaborates the structures and functions of glycoproteins; glycoproteins are common post-translationally modified proteins and are heterogeneous and non-deterministically synthesized as an evolutionarily driven mechanism that elaborates the functions of glycosylated gene products. Glycoproteins, accounting for approximately half of all proteins, require specialized proteomics data analysis methods due to micro- and macro-heterogeneities as a given glycosite can be divided into several glycosylated forms, each of which must be quantified. Sampling of heterogeneous glycopeptides is limited by mass spectrometer speed and sensitivity, resulting in missing values. In conjunction with the low sample size inherent to glycoproteomics, a specialized toolset is needed to determine if observed changes in glycopeptide abundances are biologically significant or due to data quality limitations.

Results

We developed an R package, Relative Assessment of m/z Identifications by Similarity (RAMZIS), that uses similarity metrics to guide researchers to a more rigorous interpretation of glycoproteomics data. RAMZIS uses a permutation test to generate contextual similarity, which assesses the quality of mass spectral data and outputs a graphical demonstration of the likelihood of finding biologically significant differences in glycosylation abundance datasets. Investigators can assess dataset quality, holistically differentiate glycosites, and identify which glycopeptides are responsible for glycosylation pattern change. RAMZIS is validated by theoretical cases and a proof-of-concept application. RAMZIS enables comparison between datasets too stochastic, small, or sparse for interpolation while acknowledging these issues in its assessment. Using this tool, researchers will be able to rigorously define the role of glycosylation and the changes that occur during biological processes.

Availability and implementation

https://github.com/WillHackett22/RAMZIS.

Direct and Detailed Site-Specific Glycopeptide Characterization by Higher-Energy Electron-Activated Dissociation Tandem Mass Spectrometry

Glycosylation is widely recognized as the most complex post-translational modification due to the widespread presence of macro- and microheterogeneities, wherein its biological consequence is closely related to both the glycosylation sites and the glycan fine structures. Yet, efficient site-specific detailed glycan characterization remains a significant analytical challenge. Here, utilizing an Orbitrap-Omnitrap platform, higher-energy electron-activated dissociation (heExD) tandem mass spectrometry (MS/MS) revealed extraordinary efficacy for the structural characterization of intact glycopeptides. HeExD produced extensive fragmentation within both the glycan and the peptide, including A-/B-/C-/Y-/Z-/X-ions from the glycan motif and a-/b-/c-/x-/y-/z-type peptide fragments (with or without the glycan). The intensity of cross-ring cleavage and backbone fragments retaining the intact glycan was highly dependent on the electron energy. Among the four electron energy levels investigated, electronic excitation dissociation (EED) provided the most comprehensive structural information, yielding a complete series of glycosidic fragments for accurate glycan topology determination, a wealth of cross-ring fragments for linkage definition, and the most extensive peptide backbone fragments for accurate peptide sequencing and glycosylation site localization. The glycan fragments observed in the EED spectrum correlated well with the fragmentation patterns observed in EED MS/MS of the released glycans. The advantages of EED over higher-energy collisional dissociation (HCD), stepped collision energy HCD (sceHCD), and electron-transfer/higher-energy collisional dissociation (EThcD) were demonstrated for the characterization of a glycopeptide bearing a biantennary disialylated glycan. EED can produce a complete peptide backbone and glycan sequence coverage even for doubly protonated precursors. The exceptional performance of heExD MS/MS, particularly EED MS/MS, in site-specific detailed glycan characterization on an Orbitrap-Omnitrap hybrid instrument presents a novel option for in-depth glycosylation analysis.

Proteomics-based mass spectrometry profiling of SARS-CoV-2 infection from human nasopharyngeal samples

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the cause of the on-going global pandemic of coronavirus disease 2019 (COVID-19) that continues to pose a significant threat to public health worldwide. SARS-CoV-2 encodes four structural proteins namely membrane, nucleocapsid, spike, and envelope proteins that play essential roles in viral entry, fusion, and attachment to the host cell. Extensively glycosylated spike protein efficiently binds to the host angiotensin-converting enzyme 2 initiating viral entry and pathogenesis. Reverse transcriptase polymerase chain reaction on nasopharyngeal swab is the preferred method of sample collection and viral detection because it is a rapid, specific, and high-throughput technique. Alternate strategies such as proteomics and glycoproteomics-based mass spectrometry enable a more detailed and holistic view of the viral proteins and host-pathogen interactions and help in detection of potential disease markers. In this review, we highlight the use of mass spectrometry methods to profile the SARS-CoV-2 proteome from clinical nasopharyngeal swab samples. We also highlight the necessity for a comprehensive glycoproteomics mapping of SARS-CoV-2 from biological complex matrices to identify potential COVID-19 markers.

Analysis of complex proteoglycans using serial proteolysis and EThcD provides deep N- and O-glycoproteomic coverage

Proteoglycans are a small but diverse family of proteins that play a wide variety of roles at the cell surface and in the extracellular matrix. In addition to their glycosaminoglycan (GAG) chains, they are N- and O-glycosylated. All of these types of glycosylation are crucial to their function but present a considerable analytical challenge. We describe the combination of serial proteolysis followed by the application of higher-energy collisional dissociation (HCD) and electron transfer/higher-energy collisional dissociation (EThcD) to optimize protein sequence coverage and glycopeptide identification from proteoglycans. In many cases, the use of HCD alone allows the identification of more glycopeptides. However, the localization of glycoforms on multiply glycosylated peptides has remained elusive. We demonstrate the use of EThcD for the confident assignment of glycan compositions on multiply glycosylated peptides. Dense glycosylation on proteoglycans is key to their biological function; thus, developing tools to identify and quantify doubly glycosylated peptides is of interest. Additionally, glycoproteomics searches identify glycopeptides in otherwise poorly covered regions of proteoglycans. The development of these and other analytical tools may permit glycoproteomic similarity comparisons in biological samples.

Progressive mechanical and structural changes in anterior cerebral arteries with Alzheimer's disease

Alzheimer's disease (AD) is a neurodegenerative disease and the main cause for dementia. The irreversible neurodegeneration leads to a gradual loss of brain function characterized predominantly by memory loss. Cerebrovascular changes are common neuropathologic findings in aged subjects with dementia. Cerebrovascular integrity is critical for proper metabolism and perfusion of the brain, as cerebrovascular remodeling may render the brain more susceptible to pulse pressure and may be associated with poorer cognitive performance and greater risk of cerebrovascular events. The objective of this study is to provide understanding of cerebrovascular remodeling with AD progression. Anterior cerebral arteries (ACAs) from a total of 19 brain donor participants from controls and pathologically diagnosed AD groups (early-Braak stages I-II; intermediate-Braak stages III-IV; and advanced-Braak stages V-VI) were included in this study. Mechanical testing, histology, advanced optical imaging, and mass spectrometry were performed to study the progressive structural and functional changes of ACAs with AD progression. Biaxial extension-inflation tests showed that ACAs became progressively less compliant, and the longitudinal stress in the intermediate and advanced AD groups was significantly higher than that from the control group. With pathological AD development, the inner and outer diameters of the ACAs remained almost unchanged; however, histology study revealed progressive smooth muscle cell atrophy and loss of elastic fibers which led to compromised structural integrity of the arterial wall. Multiphoton imaging demonstrated elastin degradation at the media-adventitia interface, which led to the formation of an empty band of 21.0 ± 15.4 μm and 32.8 ± 9.24 μm in width for the intermediate and advanced AD groups, respectively. Furthermore, quantitative birefringence microscopy showed disorganized adventitial collagen with AD development. Mass spectrometry analysis provided further evidence of altered collagen content and other extracellular matrix (ECM) molecule and smooth muscle cell changes that were consistent with the mechanical and structural alterations. Collectively, our study provides understanding of the mechanical and structural cerebrovascular deterioration in cerebral arteries with AD, which may be related to neurodegenration and pathology in the brain.

Mass spectrometry methods for analysis of extracellular matrix components in neurological diseases

The brain extracellular matrix (ECM) is a highly glycosylated environment and plays important roles in many processes including cell communication, growth factor binding, and scaffolding. The formation of structures such as perineuronal nets (PNNs) is critical in neuroprotection and neural plasticity, and the formation of molecular networks is dependent in part on glycans. The ECM is also implicated in the neuropathophysiology of disorders such as Alzheimer's disease (AD), Parkinson's disease (PD), and Schizophrenia (SZ). As such, it is of interest to understand both the proteomic and glycomic makeup of healthy and diseased brain ECM. Further, there is a growing need for site-specific glycoproteomic information. Over the past decade, sample preparation, mass spectrometry, and bioinformatic methods have been developed and refined to provide comprehensive information about the glycoproteome. Core ECM molecules including versican, hyaluronan and proteoglycan link proteins, and tenascin are dysregulated in AD, PD, and SZ. Glycomic changes such as differential sialylation, sulfation, and branching are also associated with neurodegeneration. A more thorough understanding of the ECM and its proteomic, glycomic, and glycoproteomic changes in brain diseases may provide pathways to new therapeutic options.

Progressive Mechanical and Structural Changes in Anterior Cerebral Arteries with Alzheimer's Disease

Alzheimer disease (AD) is a neurodegenerative disease and the main cause for dementia. The irreversible neurodegeneration leads to a gradual loss of brain function characterized predominantly by memory loss. Cerebrovascular changes are common neuropathologic findings in aged subjects with dementia. Cerebrovascular integrity is critical for proper metabolism and perfusion of the brain, as cerebrovascular remodeling may render the brain more susceptible to pulse pressure and may be associated with poorer cognitive performance and greater risk of cerebrovascular events. The objective of this study is to provide understanding of cerebrovascular remodeling with AD progression. A total of 28 brain donor participants with human anterior cerebral artery (ACA) from controls and pathologically diagnosed AD groups (early - Braak stages I-II; intermediate - Braak stages III-IV; and advanced - Braak stages V-VI) were included in this study. Mechanical testing, histology, advanced optical imaging, and mass spectrometry were performed to study the progressive structural and functional changes of ACAs with AD progression. Biaxial extension-inflation tests showed that ACAs became progressively less compliant, and the longitudinal stress in the intermediate& advanced AD groups was significantly higher than that from the control group. With pathological AD development, the inner and outer diameter of ACA remained almost unchanged; however, histology study revealed progressive smooth muscle cell atrophy and loss of elastic fibers which led to compromised structural integrity of the arterial wall. Multiphoton imaging demonstrated elastin degradation at the media-adventitia interface, which led to the formation of an empty band of 21.0 ± 15.4 μm and 32.8 ± 9.24 μm in width for the intermediate& advanced AD groups, respectively. Furthermore, quantitative birefringence microscopy showed disorganized adventitial collagen with AD development. Mass spectrometry analysis provided further evidence of altered collagen content and other extracellular matrix (ECM) molecule and smooth muscle cell changes that were consistent with the mechanical and structural alterations. Collectively, our study provides understanding of the mechanical and structural cerebrovascular deterioration in cerebral arteries with AD, which may be related to neurodegenration and pathology in the brain.

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.

RAMZIS: a bioinformatic toolkit for rigorous assessment of the alterations to glycoprotein structure that occur during biological processes

Motivation

Glycosylation elaborates the structures and functions of glycoproteins; glycoproteins are common post-translationally modified proteins and are heterogeneous and non-deterministically syn-thesized as an evolutionarily driven mechanism that elaborates the functions of glycosylated gene products. While glycoproteins account for approximately half of all proteins, their macro- and micro-heterogeneity requires specialized proteomics data analysis methods as a given glycosite can be divided into several glycosylated forms, each of which must be quantified. Sampling of heterogeneous glycopeptides is limited by mass spectrometer speed and sensitivity, resulting in missing values. In conjunction with the low sample size inherent to glycoproteomics, this necessitated specialized statistical metrics to identify if observed changes in glycopeptide abundances are biologically significant or due to data quality limitations.

Results

We developed an R package, Relative Assessment of m/z Identifications by Similarity (RAMZIS), that uses similarity metrics to guide biomedical researchers to a more rigorous interpretation of glycoproteomics data. RAMZIS uses contextual similarity to assess the quality of mass spectral data and generates graphical output that demonstrates the likelihood of finding biologically significant differences in glycosylation abundance dataset. Investigators can assess dataset quality, holistically differentiate glycosites, and identify which glycopeptides are responsible for glycosylation pattern expression change. Herein RAMZIS approach is validated by theoretical cases and by a proof-of-concept application. RAMZIS enables comparison between datasets too stochastic, small, or sparse for interpolation while acknowledging these issues in its assessment. Using our tool, researchers will be able to rigor-ously define the role of glycosylation and the changes that occur during biological processes.

The 2022 Nobel Prize in Chemistry for the development of click chemistry and bioorthogonal chemistry

The 2022 Nobel Prize in Chemistry recognized the development of biorthogonal chemical ligation reactions known as click chemistry in biomedicine. This concept has catalyzed significant progress in sensing and diagnosis, chemical biology, materials chemistry, and drug discovery and delivery. In proteomics, the ability to incorporate a click tag into proteins has propelled development of powerful new methods for selective enrichment of protein complexes that inform understanding of protein networks. It also has had a strong influence on the ability to enrich for protein post-translational modifications. This feature article summarizes the impacts of biorthogonal click chemistry on proteomics.

Glycoproteomic Analyses of Influenza A Viruses Using timsTOF Pro MS

N-Linked glycosylation in hemagglutinin and neuraminidase glycoproteins of influenza viruses affects antigenic and receptor binding properties, and precise analyses of site-specific glycoforms in these proteins are critical in understanding the antigenic and immunogenic properties of influenza viruses. In this study, we developed a glycoproteomic approach by using a timsTOF Pro mass spectrometer (MS) to determine the abundance and heterogeneity of site-specific glycosylation for influenza glycoproteins. Compared with a Q Exactive HF MS, the timsTOF Pro MS method without the hydrophilic interaction liquid chromatography column enrichment achieved similar glycopeptide coverage and quantities but was more effective in identifying low-abundance glycopeptides. We quantified the distributions of intact site-specific glycopeptides in hemagglutinin of A/chicken/Wuxi/0405005/2013 (H7N9) and A/mute swan/Rhode Island/A00325125/2008 (H7N3). Results showed that hemagglutinin for both viruses had complex N-glycans at N22, N38, N240, and N483 but only high-mannose glycans at N411 and, however, that the type and quantities of glycans were distinct between these viruses. Collisional cross section (CCS) provided by the ion mobility spectrometry from the timsTOF Pro MS data differentiated sialylation linkages of the glycopeptides. In summary, timsTOF Pro MS method can quantify intact site-specific glycans for influenza glycoproteins without enrichment and thus facilitate influenza vaccine development and production.

Methods to improve quantitative glycoprotein coverage from bottom-up LC-MS data

Advances in mass spectrometry instrumentation, methods development, and bioinformatics have greatly improved the ease and accuracy of site-specific, quantitative glycoproteomics analysis. Data-dependent acquisition is the most popular method for identification and quantification of glycopeptides; however, complete coverage of glycosylation site glycoforms remains elusive with this method. Targeted acquisition methods improve the precision and accuracy of quantification, but at the cost of throughput and discoverability. Data-independent acquisition (DIA) holds great promise for more complete and highly quantitative site-specific glycoproteomics analysis, while maintaining the ability to discover novel glycopeptides without prior knowledge. We review additional features that can be used to increase selectivity and coverage to the DIA workflow: retention time modeling, which would simplify the interpretation of complex tandem mass spectra, and ion mobility separation, which would maximize the sampling of all precursors at a giving chromatographic retention time. The instrumentation and bioinformatics to incorporate these features into glycoproteomics analysis exist. These improvements in quantitative, site-specific analysis will enable researchers to assess glycosylation similarity in related biological systems, answering new questions about the interplay between glycosylation state and biological function.

O-Glycoproteomic analysis of engineered heavily glycosylated fusion proteins using nanoHILIC-MS

Recombinant protein engineering design affects therapeutic properties including protein efficacy, safety, and immunogenicity. Importantly, glycosylation modulates glycoprotein therapeutic pharmacokinetics, pharmacodynamics, and effector functions. Furthermore, the development of fusion proteins requires in-depth characterization of the protein integrity and its glycosylation to evaluate their critical quality attributes. Fc-fusion proteins can be modified by complex glycosylation on the active peptide, the fragment crystallizable (Fc) domain, and the linker peptides. Moreover, the type of glycosylation and the glycan distribution at a given glycosite depend on the host cell line and the expression system conditions that significantly impact safety and efficacy. Because of the inherent heterogeneity of glycosylation, it is necessary to assign glycan structural detail for glycoprotein quality control. Using conventional reversed-phase LC-MS methods, the different glycoforms at a given glycosite elute over a narrow retention time window, and glycopeptide ionization is suppressed by co-eluting non-modified peptides. To overcome this drawback, we used nanoHILIC-MS to characterize the complex glycosylation of UTI-Fc, a fusion protein that greatly increases the half-life of ulinastatin. By this methodology, we identified and characterized ulinastatin glycopeptides at the Fc domain and linker peptide. The results described herein demonstrate the advantages of nanoHILIC-MS to elucidate glycan features on glycotherapeutics that fail to be detected using traditional reversed-phase glycoproteomics.

Improving Statistical Certainty of Glycosylation Similarity between Influenza A Virus Variants Using Data-Independent Acquisition Mass Spectrometry

Amino acid sequences of immunodominant domains of hemagglutinin (HA) on the surface of influenza A virus (IAV) evolve rapidly, producing viral variants. HA mediates receptor recognition, binding and cell entry, and serves as the target for IAV vaccines. Glycosylation, a post-translational modification that places large branched polysaccharide molecules on proteins, can modulate the function of HA and shield antigenic regions allowing for viral evasion from immune responses. Our previous work showed that subtle changes in the HA protein sequence can have a measurable change in glycosylation. Thus, being able to quantitatively measure glycosylation changes in variants is critical for understanding how HA function may change throughout viral evolution. Moreover, understanding quantitatively how the choice of viral expression systems affects glycosylation can help in the process of vaccine design and manufacture. Although IAV vaccines are most commonly expressed in chicken eggs, cell-based vaccines have many advantages, and the adoption of more cell-based vaccines would be an important step in mitigating seasonal influenza and protecting against future pandemics. Here, we have investigated the use of data-independent acquisition (DIA) mass spectrometry for quantitative glycoproteomics. We found that DIA improved the sensitivity of glycopeptide detection for four variants of A/Switzerland/9715293/2013 (H3N2): WT and mutant, each expressed in embryonated chicken eggs and Madin-Darby canine kidney cells. We used the Tanimoto similarity metric to quantify changes in glycosylation between WT and mutant and between egg-expressed and cell-expressed virus. Our DIA site-specific glycosylation similarity comparison of WT and mutant expressed in eggs confirmed our previous analysis while achieving greater depth of coverage. We found that sequence variations and changing viral expression systems affected distinct glycosylation sites of HA. Our methods can be applied to track glycosylation changes in circulating IAV variants to bolster genomic surveillance already being done, for a more complete understanding of IAV evolution.

Measuring change in glycoprotein structure

Biosynthetic enzymes in the secretory pathway create distributions of glycans at each glycosite that elaborate the biophysical properties and biological functions of glycoproteins. Because the biosynthetic glycosylation reactions do not go to completion, each protein glycosite is heterogeneous with respect to glycosylation. This heterogeneity means that it is not sufficient to measure protein abundance in omics experiments. Rather, it is necessary to sample the distribution of glycosylation at each glycosite to quantify the changes that occur during biological processes. On the one hand, the use of data-dependent acquisition methods to sample glycopeptides is limited by the instrument duty cycle and the missing value problem. On the other, stepped window data-independent acquisition samples all precursors, but ion abundances are limited by duty cycle. Therefore, the ability to quantify accurately the flux in glycoprotein glycosylation that occurs during biological processes requires the exploitation of emerging mass spectrometry technologies capable of deep, comprehensive sampling and selective high confidence assignment of the complex glycopeptide mixtures. This review summarizes recent technical advances and mass spectral glycoproteomics analysis strategies and how these developments impact our ability to quantify the changes in glycosylation that occur during biological processes. We highlight specific improvements to glycopeptide characterization through activated electron dissociation, ion mobility trends and instrumentation, and efficient algorithmic approaches for glycopeptide assignment. We also discuss the emerging need for unified standards to enable interlaboratory collaborations and effective monitoring of structural changes in glycoproteins.

Matrisome changes in Parkinson's disease

Extracellular matrix (ECM) proteins, collectively known as the matrisome, include collagens, glycoproteins, and proteoglycans. Alterations in the matrisome have been implicated in the neurodegenerative pathologies including Parkinson's disease (PD). In this work, we utilized our previously published PD and control proteomics data from human prefrontal cortex and focused our analysis on the matrisome. Among matrisome proteins, we observed a significant enrichment in the expression of type I collagen in PD vs. control samples. We then performed histological analysis on the same samples used for proteomics study, and examined collagen expression using picrosirius red staining. Interestingly, we observed similar trends in collagen abundance in PD vs. control as in our matrisome analysis; thus, this and other histological analyses will be useful as a complementary technique in the future to study the matrisome in PD with a larger cohort, and it may aid in choosing regions of interest for proteomic analysis. Additionally, collagen hydroxyprolination was less variable in PD compared to controls. Glycoproteomic changes in matrisome molecules were also observed in PD relative to aged individuals, especially related to type VI collagen and versican. We further examined the list of differentially expressed matrisome molecules using network topology-based analysis and found that angiogenesis indicated by alterations in decorin and several members of the collagen family was affected in PD. These findings collectively identified matrisome changes associated with PD; further studies with a larger cohort are required to validate the current results.

In-Depth Matrisome and Glycoproteomic Analysis of Human Brain Glioblastoma Versus Control Tissue

Glioblastoma (GBM) is the most common and malignant primary brain tumor. The extracellular matrix, also known as the matrisome, helps determine glioma invasion, adhesion, and growth. Little attention, however, has been paid to glycosylation of the extracellular matrix components that constitute the majority of glycosylated protein mass and presumed biological properties. To acquire a comprehensive understanding of the biological functions of the matrisome and its components, including proteoglycans (PGs) and glycosaminoglycans (GAGs), in GBM tumorigenesis, and to identify potential biomarker candidates, we studied the alterations of GAGs, including heparan sulfate (HS) and chondroitin sulfate (CS), the core proteins of PGs, and other glycosylated matrisomal proteins in GBM subtypes versus control human brain tissue samples. We scrutinized the proteomics data to acquire in-depth site-specific glycoproteomic profiles of the GBM subtypes that will assist in identifying specific glycosylation changes in GBM. We observed an increase in CS 6-O sulfation and a decrease in HS 6-O sulfation, accompanied by an increase in unsulfated CS and HS disaccharides in GBM versus control samples. Several core matrisome proteins, including PGs (decorin, biglycan, agrin, prolargin, glypican-1, and chondroitin sulfate proteoglycan 4), tenascin, fibronectin, hyaluronan link protein 1 and 2, laminins, and collagens, were differentially regulated in GBM versus controls. Interestingly, a higher degree of collagen hydroxyprolination was also observed for GBM versus controls. Further, two PGs, chondroitin sulfate proteoglycan 4 and agrin, were significantly lower, about 6-fold for isocitrate dehydrogenase-mutant, compared to the WT GBM samples. Differential regulation of O-glycopeptides for PGs, including brevican, neurocan, and versican, was observed for GBM subtypes versus controls. Moreover, an increase in levels of glycosyltransferase and glycosidase enzymes was observed for GBM when compared to control samples. We also report distinct protein, peptide, and glycopeptide features for GBM subtypes comparisons. Taken together, our study informs understanding of the alterations to key matrisomal molecules that occur during GBM development. (Data are available via ProteomeXchange with identifier PXD028931, and the peaks project file is available at Zenodo with DOI 10.5281/zenodo.5911810).

The minimum information required for a glycomics experiment (MIRAGE): reporting guidelines for capillary electrophoresis

The Minimum Information Required for a Glycomics Experiment (MIRAGE) is an initiative to standardize the reporting of glycoanalytical methods and to assess their reproducibility. To date, the MIRAGE Commission has published several reporting guidelines that describe what information should be provided for sample preparation methods, mass spectrometry methods, liquid chromatography (LC) analysis, exoglycosidase digestions, glycan microarray methods and nuclear magnetic resonance methods. Here we present the first version of reporting guidelines for glyco(proteo)mics analysis by capillary electrophoresis (CE) for standardized and high-quality reporting of experimental conditions in the scientific literature. The guidelines cover all aspects of a glyco(proteo)mics CE experiment including sample preparation, CE operation mode (CZE, CGE, CEC, MEKC, cIEF, cITP), instrument configuration, capillary separation conditions, detection, data analysis, and experimental descriptors. These guidelines are linked to other MIRAGE guidelines and are freely available through the project website https://www.beilstein-institut.de/en/projects/mirage/guidelines/#ce_analysis (doi:10.3762/mirage.7).

Resolving Heparan Sulfate Oligosaccharide Positional Isomers Using Hydrophilic Interaction Liquid Chromatography-Cyclic Ion Mobility Mass Spectrometry

Heparan sulfate (HS) is a linear polysaccharide covalently attached to proteoglycans on cell surfaces and within extracellular matrices in all animal tissues. Many biological processes are triggered by the interactions among HS binding proteins and short structural motifs in HS chains. The determination of HS oligosaccharide structures using liquid chromatography-mass spectrometry (LC-MS) is made challenging by the existence of positional sulfation and acetylation isomers. The determination of uronic acid epimer positions is even more challenging. While hydrophilic interaction liquid chromatography (HILIC) separates HS saccharides based on their composition, there is a very limited resolution of positional isomers. This lack of resolution places a burden on the tandem mass spectrometry step for assigning saccharide isomers. In this work, we explored the use of the ion mobility dimension to separate HS saccharide isomers based on molecular shape in the gas phase. We showed that the combination of HILIC and cyclic ion mobility mass spectrometry (cIM-MS) was extremely useful for resolving HS positional isomers including uronic acid epimers and sulfate positions. Furthermore, HILIC-cIM-MS differentiated multicomponent HS isomeric saccharide mixtures. In summary, HILIC-cIM-MS provided high-quality data for analysis of HS oligosaccharide isomeric mixtures that may prove useful in the discovery of new structural motifs for HS binding proteins and for the targeted quality control analysis of commercial HS products.

Community evaluation of glycoproteomics informatics solutions reveals high-performance search strategies for serum glycopeptide analysis

Glycoproteomics is a powerful yet analytically challenging research tool. Software packages aiding the interpretation of complex glycopeptide tandem mass spectra have appeared, but their relative performance remains untested. Conducted through the HUPO Human Glycoproteomics Initiative, this community study, comprising both developers and users of glycoproteomics software, evaluates solutions for system-wide glycopeptide analysis. The same mass spectrometrybased glycoproteomics datasets from human serum were shared with participants and the relative team performance for N- and O-glycopeptide data analysis was comprehensively established by orthogonal performance tests. Although the results were variable, several high-performance glycoproteomics informatics strategies were identified. Deep analysis of the data revealed key performance-associated search parameters and led to recommendations for improved 'high-coverage' and 'high-accuracy' glycoproteomics search solutions. This study concludes that diverse software packages for comprehensive glycopeptide data analysis exist, points to several high-performance search strategies and specifies key variables that will guide future software developments and assist informatics decision-making in glycoproteomics.

The Need for Community Standards to Enable Accurate Comparison of Glycoproteomics Algorithm Performance

Protein glycosylation that mediates interactions among viral proteins, host receptors, and immune molecules is an important consideration for predicting viral antigenicity. Viral spike proteins, the proteins responsible for host cell invasion, are especially important to be examined. However, there is a lack of consensus within the field of glycoproteomics regarding identification strategy and false discovery rate (FDR) calculation that impedes our examinations. As a case study in the overlap between software, here as a case study, we examine recently published SARS-CoV-2 glycoprotein datasets with four glycoproteomics identification software with their recommended protocols: GlycReSoft, Byonic, pGlyco2, and MSFragger-Glyco. These software use different Target-Decoy Analysis (TDA) forms to estimate FDR and have different database-oriented search methods with varying degrees of quantification capabilities. Instead of an ideal overlap between software, we observed different sets of identifications with the intersection. When clustering by glycopeptide identifications, we see higher degrees of relatedness within software than within glycosites. Taking the consensus between results yields a conservative and non-informative conclusion as we lose identifications in the desire for caution; these non-consensus identifications are often lower abundance and, therefore, more susceptible to nuanced changes. We conclude that present glycoproteomics softwares are not directly comparable, and that methods are needed to assess their overall results and FDR estimation performance. Once such tools are developed, it will be possible to improve FDR methods and quantify complex glycoproteomes with acceptable confidence, rather than potentially misleading broad strokes.

Selective Inhibition of Heparan Sulphate and Not Chondroitin Sulphate Biosynthesis by a Small, Soluble Competitive Inhibitor

The glycosaminoglycan, heparan sulphate (HS), orchestrates many developmental processes. Yet its biological role has not yet fully been elucidated. Small molecule chemical inhibitors can be used to perturb HS function and these compounds provide cheap alternatives to genetic manipulation methods. However, existing chemical inhibition methods for HS also interfere with chondroitin sulphate (CS), complicating data interpretation of HS function. Herein, a simple method for the selective inhibition of HS biosynthesis is described. Using endogenous metabolic sugar pathways, Ac₄GalNAz produces UDP-GlcNAz, which can target HS synthesis. Cell treatment with Ac₄GalNAz resulted in defective chain elongation of the polymer and decreased HS expression. Conversely, no adverse effect on CS production was observed. The inhibition was transient and dose-dependent, affording rescue of HS expression after removal of the unnatural azido sugar. The utility of inhibition is demonstrated in cell culture and in whole organisms, demonstrating that this small molecule can be used as a tool for HS inhibition in biological systems.

Glycoproteomic Sample Processing, LC-MS, and Data Analysis Using GlycReSoft

Identification of N- and O-glycosylation on specific sites of proteins, along with glycan structural information, is necessary to determine the roles glycoproteins play in normal and pathologic cellular functions. Because such glycosylation is macro- and micro-heterogeneous and alters the dissociation behavior of glycopeptides, specific sample preparation, mass spectrometry, and data analysis techniques are required. Advanced tandem mass spectrometry-based glycoproteomics coupled with powerful data mining algorithms are key elements for characterization of protein glycosylation. This article includes the detailed, streamlined sample preparation method for liquid chromatography-mass spectrometry data acquisition and subsequent bioinformatics-based data annotation using the publicly available GlycReSoft program for highly efficient identification and quantification of glycoprotein glycosylation. © 2021 Wiley Periodicals LLC. Basic Protocol 1: Characterization of glycans and site occupancy on purified glycoprotein Support Protocol 1: In-gel digestion of glycoproteins Support Protocol 2: Detection of glycoproteins from cells/tissue through glycopeptide enrichment Basic Protocol 2: Acquisition of glycopeptides through high-resolution nano-LC-MS/MS Basic Protocol 3: Identification and quantification of glycopeptides using GlycReSoft.

Influence of saccharide modifications on heparin lyase III substrate specificities

A library of 23 synthetic heparan sulfate (HS) oligosaccharides, varying in chain length, types and positions of modifications, was used to analyze the substrate specificities of heparin lyase III enzymes from both Flavobacterium heparinum and Bacteroides eggerthii. The influence of specific modifications, including N-substitution, 2-O sulfation, 6-O sulfation and 3-O sulfation on lyase III digestion was examined systematically. It was demonstrated that lyase III from both sources can completely digest oligosaccharides lacking O-sulfates. 2-O Sulfation completely blocked cleavage at the corresponding site; 6-O and 3-O sulfation on glucosamine residues inhibited enzyme activity. We also observed that there are differences in substrate specificities between the two lyase III enzymes for highly sulfated oligosaccharides. These findings will facilitate obtaining and analyzing the functional sulfated domains from large HS polymer, to better understand their structure/function relationships in biological processes.

Glycoproteomic Sample Processing, LC-MS, and Data Analysis Using GlycReSoft

Identification of N- and O-glycosylation on specific sites of proteins, along with glycan structural information, is necessary to determine the roles glycoproteins play in normal and pathologic cellular functions. Because such glycosylation is macro- and micro-heterogeneous and alters the dissociation behavior of glycopeptides, specific sample preparation, mass spectrometry, and data analysis techniques are required. Advanced tandem mass spectrometry-based glycoproteomics coupled with powerful data mining algorithms are key elements for characterization of protein glycosylation. This article includes the detailed, streamlined sample preparation method for liquid chromatography-mass spectrometry data acquisition and subsequent bioinformatics-based data annotation using the publicly available GlycReSoft program for highly efficient identification and quantification of glycoprotein glycosylation. © 2021 Wiley Periodicals LLC. Basic Protocol 1: Characterization of glycans and site occupancy on purified glycoprotein Support Protocol 1: In-gel digestion of glycoproteins Support Protocol 2: Detection of glycoproteins from cells/tissue through glycopeptide enrichment Basic Protocol 2: Acquisition of glycopeptides through high-resolution nano-LC-MS/MS Basic Protocol 3: Identification and quantification of glycopeptides using GlycReSoft.

Expression of the Extracellular Sulfatase SULF2 Affects Survival of Head and Neck Squamous Cell Carcinoma Patients

Sulfation of heparan sulfate proteoglycans (HSPG) regulates signaling of growth factor receptors via specific interactions with the sulfate groups. 6-O-Sulfation of HSPG is an impactful modification regulated by the activities of dedicated extracellular endosulfatases. Specifically, extracellular sulfatase Sulf-2 (SULF2) removes 6-O-sulfate from HS chains, modulates affinity of carrier HSPG to their ligands, and thereby influences activity of the downstream signaling pathway. In this study, we explored the effect of SULF2 expression on HSPG sulfation and its relationship to clinical outcomes of patients with head and neck squamous cell carcinoma (HNSCC). We found a significant overexpression of SULF2 in HNSCC tumor tissues which differs by tumor location and etiology. Expression of SULF2 mRNA in tumors associated with human papillomavirus (HPV) infection was two-fold lower than in tumors associated with a history of tobacco and alcohol consumption. High SULF2 mRNA expression is significantly correlated with poor progression-free interval and overall survival of patients (n = 499). Among all HS-related enzymes, SULF2 expression had the highest hazard ratio in overall survival after adjusting for clinical characteristics. SULF2 protein expression (n = 124), determined by immunohistochemical analysis, showed a similar trend. The content of 6-O-sulfated HSPG, measured by staining with the HS3A8 antibody, was higher in adjacent mucosa compared to tumor tissue but revealed no difference based on SULF2 staining. LC-MS/MS analysis showed low abundance of N-sulfation and O-sulfation in HS but no significant difference between SULF2-positive and SULF2-negative tumors. Levels of enzymes modifying 6-O-sulfation, measured by RT-qPCR in HNSCC tumor tissues, suggest that HSPG sulfation is carried out by the co-regulated activities of multiple genes. Imbalance of the HS modifying enzymes in HNSCC tumors modifies the overall sulfation pattern, but the alteration of 6-O-sulfate is likely non-uniform and occurs in specific domains of the HS chains. These findings demonstrate that SULF2 expression correlates with survival of HNSCC patients and could potentially serve as a prognostic factor or target of therapeutic interventions.

Calculating Glycoprotein Similarities From Mass Spectrometric Data

Complex protein glycosylation occurs through biosynthetic steps in the secretory pathway that create macro- and microheterogeneity of structure and function. Required for all life forms, glycosylation diversifies and adapts protein interactions with binding partners that underpin interactions at cell surfaces and pericellular and extracellular environments. Because these biological effects arise from heterogeneity of structure and function, it is necessary to measure their changes as part of the quest to understand nature. Quite often, however, the assumption behind proteomics that posttranslational modifications are discrete additions that can be modeled using the genome as a template does not apply to protein glycosylation. Rather, it is necessary to quantify the glycosylation distribution at each glycosite and to aggregate this information into a population of mature glycoproteins that exist in a given biological system. To date, mass spectrometric methods for assigning singly glycosylated peptides are well-established. But it is necessary to quantify glycosylation heterogeneity accurately in order to gauge the alterations that occur during biological processes. The task is to quantify the glycosylated peptide forms as accurately as possible and then apply appropriate bioinformatics algorithms to the calculation of micro- and macro-similarities. In this review, we summarize current approaches for protein quantification as they apply to this glycoprotein similarity problem.

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.

Glycosylation of Serum Clusterin in Wild-Type Transthyretin-Associated (ATTRwt) Amyloidosis: A Study of Disease-Associated Compositional Features Using Mass Spectrometry Analyses

Wild-type transthyretin-associated (ATTRwt) amyloidosis is an age-related disease that causes heart failure in older adults. This disease frequently features cardiac amyloid fibril deposits that originate from dissociation of the tetrameric protein, transthyretin (TTR). Unlike hereditary TTR (ATTRm) amyloidosis, where amino acid replacements destabilize the native protein, in ATTRwt amyloidosis, amyloid-forming TTR lacks protein sequence alterations. The initiating cause of fibril formation in ATTRwt amyloidosis is unclear, and thus, it seems plausible that other factors are involved in TTR misfolding and unregulated accumulation of wild-type TTR fibrils. We believe that clusterin (CLU, UniProtKB P10909), a plasma circulating glycoprotein, plays a role in the pathobiology of ATTRwt amyloidosis. Previously, we have suggested a role for CLU in ATTRwt amyloidosis based on our studies showing that (1) CLU codeposits with non-native TTR in amyloid fibrils from ATTRwt cardiac tissue, (2) CLU interacts only with non-native (monomeric and aggregated) forms of TTR, and (3) CLU serum levels in patients with ATTRwt are significantly lower compared to healthy controls. In the present study, we provide comprehensive detail of compositional findings from mass spectrometry analyses of amino acid and glycan content of CLU purified from ATTRwt and control sera. The characterization of oligosaccharide content in serum CLU derived from patients with ATTRwt amyloidosis is novel data. Moreover, results comparing CLU oligosaccharide variations between patient and healthy controls are original and provide further evidence for the role of CLU in ATTRwt pathobiology, possibly linked to disease-specific structural features that limit the chaperoning capacity of CLU.

Measuring Site-specific Glycosylation Similarity between Influenza a Virus Variants with Statistical Certainty

Influenza A virus (IAV) mutates rapidly, resulting in antigenic drift and poor year-to-year vaccine effectiveness. One challenge in designing effective vaccines is that genetic mutations frequently cause amino acid variations in IAV envelope protein hemagglutinin (HA) that create new N-glycosylation sequons; resulting N-glycans cause antigenic shielding, allowing viral escape from adaptive immune responses. Vaccine candidate strain selection currently involves correlating antigenicity with HA protein sequence among circulating strains, but quantitative comparison of site-specific glycosylation information may likely improve the ability to design vaccines with broader effectiveness against evolving strains. However, there is poor understanding of the influence of glycosylation on immunodominance, antigenicity, and immunogenicity of HA, and there are no well-tested methods for comparing glycosylation similarity among virus samples. Here, we present a method for statistically rigorous quantification of similarity between two related virus strains that considers the presence and abundance of glycopeptide glycoforms. We demonstrate the strength of our approach by determining that there was a quantifiable difference in glycosylation at the protein level between WT IAV HA from A/Switzerland/9715293/2013 (SWZ13) and a mutant strain of SWZ13, even though no N-glycosylation sequons were changed. We determined site-specifically that WT and mutant HA have varying similarity at the glycosylation sites of the head domain, reflecting competing pressures to evade host immune response while retaining viral fitness. To our knowledge, our results are the first to quantify changes in glycosylation state that occur in related proteins of considerable glycan heterogeneity. Our results provide a method for understanding how changes in glycosylation state are correlated with variations in protein sequence, which is necessary for improving IAV vaccine strain selection. Understanding glycosylation will be especially important as we find new expression vectors for vaccine production, as glycosylation state depends greatly on the host species.

A glycomics and proteomics study of aging and Parkinson's disease in human brain

Previous studies on Parkinson’s disease mechanisms have shown dysregulated extracellular transport of α-synuclein and growth factors in the extracellular space. In the human brain these consist of perineuronal nets, interstitial matrices, and basement membranes, each composed of a set of collagens, non-collagenous glycoproteins, proteoglycans, and hyaluronan. The manner by which amyloidogenic proteins spread extracellularly, become seeded, oligomerize, and are taken up by cells, depends on intricate interactions with extracellular matrix molecules. We sought to assess the alterations to structure of glycosaminoglycans and proteins that occur in PD brain relative to controls of similar age. We found that PD differs markedly from normal brain in upregulation of extracellular matrix structural components including collagens, proteoglycans and glycosaminoglycan binding molecules. We also observed that levels of hemoglobin chains, possibly related to defects in iron metabolism, were enriched in PD brains. These findings shed important new light on disease processes that occur in association with PD.

Complexity and ultrastructure of infectious extracellular vesicles from cells infected by non-enveloped virus

Enteroviruses support cell-to-cell viral transmission prior to their canonical lytic spread of virus. Poliovirus (PV), a prototype for human pathogenic positive-sense RNA enteroviruses, and picornaviruses in general, transport multiple virions en bloc via infectious extracellular vesicles, 100~1000 nm in diameter, secreted from host cells. Using biochemical and biophysical methods we identify multiple components in secreted microvesicles, including mature PV virions; positive-sense genomic and negative-sense replicative, template viral RNA; essential viral replication proteins; and cellular proteins. Using cryo-electron tomography, we visualize the near-native three-dimensional architecture of secreted infectious microvesicles containing both virions and a unique morphological component that we describe as a mat-like structure. While the composition of these mat-like structures is not yet known, based on our biochemical data they are expected to be comprised of unencapsidated RNA and proteins. In addition to infectious microvesicles, CD9-positive exosomes released from PV-infected cells are also infectious and transport virions. Thus, our data show that, prior to cell lysis, non-enveloped viruses are secreted within infectious vesicles that also transport viral unencapsidated RNAs, viral and host proteins. Understanding the structure and function of these infectious particles helps elucidate the mechanism by which extracellular vesicles contribute to the spread of non-enveloped virus infection.

Multi-task learning sparse group lasso: a method for quantifying antigenicity of influenza A(H1N1) virus using mutations and variations in glycosylation of Hemagglutinin

BACKGROUND

In addition to causing the pandemic influenza outbreaks of 1918 and 2009, subtype H1N1 influenza A viruses (IAVs) have caused seasonal epidemics since 1977. Antigenic property of influenza viruses are determined by both protein sequence and N-linked glycosylation of influenza glycoproteins, especially hemagglutinin (HA). The currently available computational methods are only considered features in protein sequence but not N-linked glycosylation.

RESULTS

A multi-task learning sparse group least absolute shrinkage and selection operator (LASSO) (MTL-SGL) regression method was developed and applied to derive two types of predominant features including protein sequence and N-linked glycosylation in hemagglutinin (HA) affecting variations in serologic data for human and swine H1N1 IAVs. Results suggested that mutations and changes in N-linked glycosylation sites are associated with the rise of antigenic variants of H1N1 IAVs. Furthermore, the implicated mutations are predominantly located at five reported antibody-binding sites, and within or close to the HA receptor binding site. All of the three N-linked glycosylation sites (i.e. sequons NCSV at HA 54, NHTV at HA 125, and NLSK at HA 160) identified by MTL-SGL to determine antigenic changes were experimentally validated in the H1N1 antigenic variants using mass spectrometry analyses. Compared with conventional sparse learning methods, MTL-SGL achieved a lower prediction error and higher accuracy, indicating that grouped features and MTL in the MTL-SGL method are not only able to handle serologic data generated from multiple reagents, supplies, and protocols, but also perform better in genetic sequence-based antigenic quantification.

CONCLUSIONS

In summary, the results of this study suggest that mutations and variations in N-glycosylation in HA caused antigenic variations in H1N1 IAVs and that the sequence-based antigenicity predictive model will be useful in understanding antigenic evolution of IAVs.

Serial in-solution digestion protocol for mass spectrometry-based glycomics and proteomics analysis

Advancement in mass spectrometry has revolutionized the field of proteomics. However, there remains a gap in the analysis of protein post-translational modifications (PTMs), particularly for glycosylation. Glycosylation, the most common form of PTM, is involved in most biological processes; thus, analysis of glycans along with proteins is crucial to answering important biologically relevant questions. Of particular interest is the brain extracellular matrix (ECM), which has been called the "final Frontier" in neuroscience, which consists of highly glycosylated proteins. Among these, proteoglycans (PGs) contain large glycan structures called glycosaminoglycans (GAGs) that form crucial ECM components, including perineuronal nets (PNNs), shown to be altered in neuropsychiatric diseases. Thus, there is a growing need for high-throughput methods that combine GAG (glycomics) and PGs (proteomics) analysis to unravel the complete biological picture. The protocol presented here integrates glycomics and proteomics to analyze multiple classes of biomolecules. We use a filter-aided sample preparation (FASP) type serial in-solution digestion of GAG classes, including hyaluronan (HA), chondroitin sulfate (CS), and heparan sulfate (HS), followed by peptides. The GAGs and peptides are then cleaned and analyzed using liquid chromatography-tandem mass spectrometry (LC-MS/MS). This protocol is an efficient and economical way of processing tissue or cell lysates to isolate various GAG classes and peptides from the same sample. The method is more efficient (single-pot) than available parallel (multi-pot) release methods, and removal of GAGs facilitates the identification of the proteins with higher peptide-coverage than using conventional-proteomics. Overall, we demonstrate a high-throughput & efficient protocol for mass spectrometry-based glycomic and proteomic analysis (data are available via ProteomeXchange with identifier PXD017513).

Proteomic and biological profiling of extracellular vesicles from Alzheimer's disease human brain tissues

Introduction

Extracellular vesicles (EVs) from human Alzheimer's disease (AD) biospecimens contain amyloid beta (Aβ) peptide and tau. While AD EVs are known to affect brain disease pathobiology, their biochemical and molecular characterizations remain ill defined.

Methods

EVs were isolated from the cortical gray matter of 20 AD and 18 control brains. Tau and Aβ levels were measured by immunoassay. Differentially expressed EV proteins were assessed by quantitative proteomics and machine learning.

Results

Levels of pS396 tau and Aβ1–42 were significantly elevated in AD EVs. High levels of neuron‐ and glia‐specific factors are detected in control and AD EVs, respectively. Machine learning identified ANXA5, VGF, GPM6A, and ACTZ in AD EV compared to controls. They distinguished AD EVs from controls in the test sets with 88% accuracy.

Discussion

In addition to Aβ and tau, ANXA5, VGF, GPM6A, and ACTZ are new signature proteins in AD EVs.

Relative Retention Time Estimation Improves N-Glycopeptide Identifications by LC-MS/MS

Glycopeptides identified by tandem mass spectrometry rely on the identification of the peptide backbone sequence and the attached glycan(s) by the incomplete fragmentation of both moieties. This may lead to ambiguous identifications where multiple structures could explain the same spectrum equally well due to missing information in the mass spectrum or incorrect precursor mass determination. To date, approaches to solving these problems have been limited, and few inroads have been made to address these issues. We present a technique to address some of these challenges and demonstrate it on previously published data sets. We use a linear modeling approach to learn the influence of the glycan composition on the retention time of a glycopeptide and use these models to validate glycopeptides within the same experiment, detecting over 400 incorrect cases during the MS/MS search and correcting 75 cases that could not be identified based on mass alone. We make this technique available as a command line executable program, written in Python and C, freely available at https://github.com/mobiusklein/glycresoft in source form, with precompiled binaries for Windows.

Toward Automatic and Comprehensive Glycan Characterization by Online PGC-LC-EED MS/MS

Despite the recent advances in mass spectrometry (MS)-based methods for glycan structural analysis, characterization of glycomes remains a significant analytical challenge, in part due to the widespread presence of isomeric structures and the need to define the many structural variables for each glycan. Interpretation of the complex tandem mass spectra of glycans is often laborious and requires substantial expertise. Broad adoption of MS methods for glycomics, within and outside the glycoscience community, has been hindered by the shortage of bioinformatics tools for rapid and accurate glycan sequencing. Here, we developed an online porous graphitic carbon liquid chromatography (PGC-LC)-electronic excitation dissociation (EED) MS/MS method that takes advantage of the superior isomer resolving power of PGC and the structural details provided by EED MS/MS for characterization of glycan mixtures. We also made improvements to GlycoDeNovo, our de novo glycan sequencing algorithm, so that it can automatically and accurately identify glycan topologies from EED tandem mass spectra acquired online. The majority of linkages can also be determined de novo, although in some cases, biological insight may be needed to fully define the glycan structure. Application of this method to the analysis of N-glycans released from ribonuclease B not only revealed the presence of 18 high-mannose structures, including new isomers not previously reported, but also provided relative quantification for each isomeric structure. With fully automated data acquisition and topology analysis, the approach presented here holds great potential for automated and comprehensive glycan characterization.

NIST Interlaboratory Study on Glycosylation Analysis of Monoclonal Antibodies: Comparison of Results from Diverse Analytical Methods

Glycosylation is a topic of intense current interest in the development of biopharmaceuticals because it is related to drug safety and efficacy. This work describes results of an interlaboratory study on the glycosylation of the Primary Sample (PS) of NISTmAb, a monoclonal antibody reference material. Seventy-six laboratories from industry, university, research, government, and hospital sectors in Europe, North America, Asia, and Australia submitted a total of 103 reports on glycan distributions. The principal objective of this study was to report and compare results for the full range of analytical methods presently used in the glycosylation analysis of mAbs. Therefore, participation was unrestricted, with laboratories choosing their own measurement techniques. Protein glycosylation was determined in various ways, including at the level of intact mAb, protein fragments, glycopeptides, or released glycans, using a wide variety of methods for derivatization, separation, identification, and quantification. Consequently, the diversity of results was enormous, with the number of glycan compositions identified by each laboratory ranging from 4 to 48. In total, one hundred sixteen glycan compositions were reported, of which 57 compositions could be assigned consensus abundance values. These consensus medians provide community-derived values for NISTmAb PS. Agreement with the consensus medians did not depend on the specific method or laboratory type. The study provides a view of the current state-of-the-art for biologic glycosylation measurement and suggests a clear need for harmonization of glycosylation analysis methods.

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.

Why Glycosylation Matters in Building a Better Flu Vaccine

Low vaccine efficacy against seasonal influenza A virus (IAV) stems from the ability of the virus to evade existing immunity while maintaining fitness. Although most potent neutralizing antibodies bind antigenic sites on the globular head domain of the IAV envelope glycoprotein hemagglutinin (HA), the error-prone IAV polymerase enables rapid evolution of key antigenic sites, resulting in immune escape. Significantly, the appearance of new N-glycosylation consensus sequences (sequons, NXT/NXS, rarely NXC) on the HA globular domain occurs among the more prevalent mutations as an IAV strain undergoes antigenic drift. The appearance of new glycosylation shields underlying amino acid residues from antibody contact, tunes receptor specificity, and balances receptor avidity with virion escape, all of which help maintain viral propagation through seasonal mutations. The World Health Organization selects seasonal vaccine strains based on information from surveillance, laboratory, and clinical observations. Although the genetic sequences are known, mature glycosylated structures of circulating strains are not defined. In this review, we summarize mass spectrometric methods for quantifying site-specific glycosylation in IAV strains and compare the evolution of IAV glycosylation to that of human immunodeficiency virus. We argue that the determination of site-specific glycosylation of IAV glycoproteins would enable development of vaccines that take advantage of glycosylation-dependent mechanisms whereby virus glycoproteins are processed by antigen presenting cells.