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Wei J, Tang Y, Bai Y, Zaia J, Costello CE, Hong P, Lin C. Toward Automatic and Comprehensive Glycan Characterization by Online PGC-LC-EED MS/MS. Anal Chem 2020; 92:782-791. [PMID: 31829560 PMCID: PMC7082718 DOI: 10.1021/acs.analchem.9b03183] [Citation(s) in RCA: 44] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/18/2022]
Abstract
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.
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De Leoz MLA, Duewer DL, Fung A, Liu L, Yau HK, Potter O, Staples GO, Furuki K, Frenkel R, Hu Y, Sosic Z, Zhang P, Altmann F, Grunwald-Grube C, Shao C, Zaia J, Evers W, Pengelley S, Suckau D, Wiechmann A, Resemann A, Jabs W, Beck A, Froehlich JW, Huang C, Li Y, Liu Y, Sun S, Wang Y, Seo Y, An HJ, Reichardt NC, Ruiz JE, Archer-Hartmann S, Azadi P, Bell L, Lakos Z, An Y, Cipollo JF, Pucic-Bakovic M, Štambuk J, Lauc G, Li X, Wang PG, Bock A, Hennig R, Rapp E, Creskey M, Cyr TD, Nakano M, Sugiyama T, Leung PKA, Link-Lenczowski P, Jaworek J, Yang S, Zhang H, Kelly T, Klapoetke S, Cao R, Kim JY, Lee HK, Lee JY, Yoo JS, Kim SR, Suh SK, de Haan N, Falck D, Lageveen-Kammeijer GSM, Wuhrer M, Emery RJ, Kozak RP, Liew LP, Royle L, Urbanowicz PA, Packer NH, Song X, Everest-Dass A, Lattová E, Cajic S, Alagesan K, Kolarich D, Kasali T, Lindo V, Chen Y, Goswami K, Gau B, Amunugama R, Jones R, Stroop CJM, Kato K, Yagi H, Kondo S, Yuen CT, Harazono A, Shi X, Magnelli PE, Kasper BT, Mahal L, Harvey DJ, O'Flaherty R, Rudd PM, Saldova R, Hecht ES, Muddiman DC, Kang J, Bhoskar P, Menard D, Saati A, Merle C, Mast S, Tep S, Truong J, Nishikaze T, Sekiya S, Shafer A, Funaoka S, Toyoda M, de Vreugd P, Caron C, Pradhan P, Tan NC, Mechref Y, Patil S, Rohrer JS, Chakrabarti R, Dadke D, Lahori M, Zou C, Cairo C, Reiz B, Whittal RM, Lebrilla CB, Wu L, Guttman A, Szigeti M, Kremkow BG, Lee KH, Sihlbom C, Adamczyk B, Jin C, Karlsson NG, Örnros J, Larson G, Nilsson J, Meyer B, Wiegandt A, Komatsu E, Perreault H, Bodnar ED, Said N, Francois YN, Leize-Wagner E, Maier S, Zeck A, Heck AJR, Yang Y, Haselberg R, Yu YQ, Alley W, Leone JW, Yuan H, Stein SE. NIST Interlaboratory Study on Glycosylation Analysis of Monoclonal Antibodies: Comparison of Results from Diverse Analytical Methods. Mol Cell Proteomics 2020; 19:11-30. [PMID: 31591262 PMCID: PMC6944243 DOI: 10.1074/mcp.ra119.001677] [Citation(s) in RCA: 67] [Impact Index Per Article: 16.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/24/2019] [Revised: 08/26/2019] [Indexed: 01/24/2023] Open
Abstract
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.
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Klein JA, Zaia J. A Perspective on the Confident Comparison of Glycoprotein Site-Specific Glycosylation in Sample Cohorts. Biochemistry 2019; 59:3089-3097. [PMID: 31833756 DOI: 10.1021/acs.biochem.9b00730] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
Abstract
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.
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Chang D, Zaia J. Why Glycosylation Matters in Building a Better Flu Vaccine. Mol Cell Proteomics 2019; 18:2348-2358. [PMID: 31604803 PMCID: PMC6885707 DOI: 10.1074/mcp.r119.001491] [Citation(s) in RCA: 47] [Impact Index Per Article: 9.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/08/2019] [Revised: 08/18/2019] [Indexed: 12/20/2022] Open
Abstract
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.
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Raghunathan R, Sethi MK, Klein JA, Zaia J. Proteomics, Glycomics, and Glycoproteomics of Matrisome Molecules. Mol Cell Proteomics 2019; 18:2138-2148. [PMID: 31471497 PMCID: PMC6823855 DOI: 10.1074/mcp.r119.001543] [Citation(s) in RCA: 34] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/03/2019] [Revised: 08/26/2019] [Indexed: 12/21/2022] Open
Abstract
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.
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Klein J, Carvalho L, Zaia J. Application of network smoothing to glycan LC-MS profiling. Bioinformatics 2019; 34:3511-3518. [PMID: 29790907 DOI: 10.1093/bioinformatics/bty397] [Citation(s) in RCA: 36] [Impact Index Per Article: 7.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/18/2017] [Accepted: 05/10/2018] [Indexed: 11/14/2022] Open
Abstract
Motivation Glycosylation is one of the most heterogeneous and complex protein post-translational modifications. Liquid chromatography coupled mass spectrometry (LC-MS) is a common high throughput method for analyzing complex biological samples. Accurate study of glycans require high resolution mass spectrometry. Mass spectrometry data contains intricate sub-structures that encode mass and abundance, requiring several transformations before it can be used to identify biological molecules, requiring automated tools to analyze samples in a high throughput setting. Existing tools for interpreting the resulting data do not take into account related glycans when evaluating individual observations, limiting their sensitivity. Results We developed an algorithm for assigning glycan compositions from LC-MS data by exploring biosynthetic network relationships among glycans. Our algorithm optimizes a set of likelihood scoring functions based on glycan chemical properties but uses network Laplacian regularization and optionally prior information about expected glycan families to smooth the likelihood and thus achieve a consistent and more representative solution. Our method was able to identify as many, or more glycan compositions compared to previous approaches, and demonstrated greater sensitivity with regularization. Our network definition was tailored to N-glycans but the method may be applied to glycomics data from other glycan families like O-glycans or heparan sulfate where the relationships between compositions can be expressed as a graph. Availability and implementation Built Executable http://www.bumc.bu.edu/msr/glycresoft/ and Source Code: https://github.com/BostonUniversityCBMS/glycresoft. Supplementary information Supplementary data are available at Bioinformatics online.
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Raghunathan R, Sethi MK, Zaia J. On-slide tissue digestion for mass spectrometry based glycomic and proteomic profiling. MethodsX 2019; 6:2329-2347. [PMID: 31660297 PMCID: PMC6807300 DOI: 10.1016/j.mex.2019.09.029] [Citation(s) in RCA: 20] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/07/2019] [Accepted: 09/23/2019] [Indexed: 12/11/2022] Open
Abstract
We describe a protocol for glycomic and proteomic profiling that uses serial enzyme digestions from the surface of fresh frozen or fixed tissue slides. The abundances of the extracted glycans and peptides are determined using liquid chromatography-mass spectrometry. In a typical experiment, our method quantifies 14 heparan sulfate disaccharides, 11 chondroitin sulfate disaccharides, 50 N-glycan compositions and approximately 1200 proteins from a 1.8 mm circle, on the surface of a fresh frozen tissue slide from rat brain. Each enzymatic digestion is incubated overnight with direct application of enzyme on the tissue surface. Overall, the sample preparation process for multiple tissue slides takes a day per biomolecule class. This protocol saves time by simultaneous digestion of large N-glycans and small HS disaccharides and subsequent separation using size exclusion chromatography. Compared to wet tissue analysis, this method requires less time by a factor of two. By comparison, MALDI-imaging provides higher spatial resolution of glycans and proteins but lower depth of coverage. MALDI dissociates fragile glycan substituents including sulfates and is not recommended for analysis of glycosaminoglycans (GAGs).
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Jacobsen Á, Shi X, Shao C, Eysturskarδ J, Mikalsen SO, Zaia J. Characterization of Glycosaminoglycans in Gaping and Intact Connective Tissues of Farmed Atlantic Salmon ( Salmo salar) Fillets by Mass Spectrometry. ACS OMEGA 2019; 4:15337-15347. [PMID: 31572832 PMCID: PMC6761683 DOI: 10.1021/acsomega.9b01136] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 04/19/2019] [Accepted: 08/22/2019] [Indexed: 06/10/2023]
Abstract
In the Atlantic salmon (Salmo salar) aquaculture industry, gaping (the separation of muscle bundles from the connective tissue) is a major quality problem. This study characterized chondroitin sulfate (CS) and heparan sulfate (HS) in the connective tissue of intact and gaping salmon fillets from 30 salmon by mass spectrometry. Statistical difference was detected between gaping and intact tissues only when comparing pairwise samples from the same individual (n = 10). The gaping tissue had a lower content of monosulfated CS disaccharides (p = 0.027), and the relative distribution of CS disaccharides was significantly different (p < 0.05). The HS chains were short (average = 14.09, SD = 4.91), and the intact tissue seemed to have a more uniform HS chain structure compared to the gaping tissue. Time-series samples from the same individuals are recommended for future research to improve the understanding of reasons and implications of these differences.
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Abstract
Heparan sulfate (HS) mediates a wide range of protein binding interactions key to normal and pathological physiology. Though liquid chromatography coupled with mass spectrometry (LC-MS) based disaccharide composition analysis is able to profile changes in HS composition, the heterogeneity of modifications and the labile sulfate group present major challenges for liquid chromatography tandem mass spectrometry (LC-MS/MS) sequencing of the HS oligosaccharides that represent protein binding determinants. Here, we report online LC-MS/MS sequencing of HS oligosaccharides using hydrophilic interaction liquid chromatography (HILIC) and negative electron transfer dissociation (NETD). A series of synthetic HS oligosaccharides varying in chain length (tetramers and hexamers), number of sulfate groups (3-7), sulfate patterns (sulfate positional isomers), and uronic acid epimerization (epimers) were separated and sequenced. The LC elution order of isomeric compounds was associated with their fine structure. The application of an online cation exchange device (ion suppressor) enhanced the precursor charge states, and the subsequent NETD produced abundant glycosidic fragments, allowing the characterization of both lowly sulfated and highly sulfated HS oligosaccharides. Furthermore, the diagnostic cross-ring ions differentiated the 6-O sulfation and 3-O sulfation, allowing unambiguous structural assignment. Collectively, this LC-NETD-MS/MS method is a powerful tool for sequencing of heterogeneous HS mixtures and is applicable for the differentiation of both isomers and epimers, for the characterization of saccharide mixtures with a varying extent of sulfation and even for the determination of both predominant and rare modification motifs. Thus, LC-NETD-MS/MS has great potential for further application to biological studies.
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Abstract
Glycoinformatics is a critical resource for the study of glycobiology, and glycobiology is a necessary component for understanding the complex interface between intra- and extracellular spaces. Despite this, there is limited software available to scientists studying these topics, requiring each to create fundamental data structures and representations anew for each of their applications. This leads to poor uptake of standardization and loss of focus on the real problems. We present glypy, a library written in Python for reading, writing, manipulating, and transforming glycans at several levels of precision. In addition to understanding several common formats for textual representation of glycans, the library also provides application programming interfaces (APIs) for major community databases, including GlyTouCan and UnicarbKB. The library is freely available under the Apache 2 common license with source code available at https://github.com/mobiusklein/ and documentation at https://glypy.readthedocs.io/ .
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Muraoka S, DeLeo AM, Sethi MK, Hogan JD, Yang Z, Ruan Z, You Y, Yukawa K, Kalava SV, Ikezu S, Ko J, Zaia J, Issadore D, Gorantla S, Gendelman HE, Ikezu T. O1‐01‐04: IDENTIFICATION AND BIOLOGICAL CHARACTERIZATION OF EXTRACELLULAR VESICLE PROTEINS FOR PROPAGATION AND SPREAD OF TAU. Alzheimers Dement 2019. [DOI: 10.1016/j.jalz.2019.06.4520] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/27/2022]
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Klein J, Zaia J. psims - A Declarative Writer for mzML and mzIdentML for Python. Mol Cell Proteomics 2019; 18:571-575. [PMID: 30563850 PMCID: PMC6398200 DOI: 10.1074/mcp.rp118.001070] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/12/2018] [Revised: 12/12/2018] [Indexed: 01/04/2023] Open
Abstract
mzML and mzIdentML are commonly used, powerful tools for representing mass spectrometry data and derived identification information. These formats are complex, requiring non-trivial logic to translate data into the appropriate representation. Most published implementations are tightly coupled to data structures. The most complete implementations are written in compiled languages that cannot expose the complete flexibility of the implementation to external programs or bindings. To our knowledge, there are no complete implementations for mzML or mzIdentML available to scripting languages like Python or R. We present psims, a library written in Python for writing mzML and mzIdentML. The library allows writing either XML format using built-in Python data structures. It includes a controlled vocabulary resolution system to simplify the encoding process and an identity tracking system to manage entity relationships. The source code is available at https://github.com/mobiusklein/psims, and through the Python Package Index as psims, licensed under the Apache 2 common license.
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Wei J, Wu J, Tang Y, Ridgeway ME, Park MA, Costello CE, Zaia J, Lin C. Characterization and Quantification of Highly Sulfated Glycosaminoglycan Isomers by Gated-Trapped Ion Mobility Spectrometry Negative Electron Transfer Dissociation MS/MS. Anal Chem 2019; 91:2994-3001. [PMID: 30649866 DOI: 10.1021/acs.analchem.8b05283] [Citation(s) in RCA: 51] [Impact Index Per Article: 10.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/08/2023]
Abstract
Glycosaminoglycans (GAGs) play vital roles in many biological processes and are naturally present as complex mixtures of polysaccharides with tremendous structural heterogeneity, including many structural isomers. Mass spectrometric analysis of GAG isomers, in particular highly sulfated heparin (Hep) and heparan sulfate (HS), is challenging because of their structural similarity and facile sulfo losses during analysis. Herein, we show that highly sulfated Hep/HS isomers may be resolved by gated-trapped ion mobility spectrometry (gated-TIMS) with negligible sulfo losses. Subsequent negative electron transfer dissociation (NETD) tandem mass spectrometry (MS/MS) analysis of TIMS-separated Hep/HS isomers generated extensive glycosidic and cross-ring fragments for confident isomer differentiation and structure elucidation. The high mobility resolution and preservation of labile sulfo modifications afforded by gated-TIMS MS analysis also allowed relative quantification of highly sulfated heparin isomers. These results show that the gated-TIMS-NETD MS/MS approach is useful for both qualitative and quantitative analysis of highly sulfated Hep/HS compounds in a manner not possible with other techniques.
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Wu ZL, Person AD, Anderson M, Burroughs B, Tatge T, Khatri K, Zou Y, Wang L, Geders T, Zaia J, Sackstein R. Imaging specific cellular glycan structures using glycosyltransferases via click chemistry. Glycobiology 2018; 28:69-79. [PMID: 29186441 PMCID: PMC5993098 DOI: 10.1093/glycob/cwx095] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/29/2017] [Accepted: 11/22/2017] [Indexed: 12/21/2022] Open
Abstract
Heparan sulfate (HS) is a polysaccharide fundamentally important for biologically activities. T/Tn antigens are universal carbohydrate cancer markers. Here, we report the specific imaging of these carbohydrates using a mesenchymal stem cell line and human umbilical vein endothelial cells (HUVEC). The staining specificities were demonstrated by comparing imaging of different glycans and validated by either removal of target glycans, which results in loss of signal, or installation of target glycans, which results in gain of signal. As controls, representative key glycans including O-GlcNAc, lactosaminyl glycans and hyaluronan were also imaged. HS staining revealed novel architectural features of the extracellular matrix (ECM) of HUVEC cells. Results from T/Tn antigen staining suggest that O-GalNAcylation is a rate-limiting step for O-glycan synthesis. Overall, these highly specific approaches for HS and T/Tn antigen imaging should greatly facilitate the detection and functional characterization of these biologically important glycans.
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DeLeo AM, Sethi M, Muraoka S, Ruan Z, Ikezu S, Golantla S, Gendelman HE, Zaia J, Ikezu T. O2‐01‐02: CHARACTERIZATION OF HUMAN ALZHEIMER'S DISEASE BRAIN‐DERIVED EXOSOMES. Alzheimers Dement 2018. [DOI: 10.1016/j.jalz.2018.06.2640] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/28/2022]
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Raghunathan R, Polinski NK, Klein JA, Hogan JD, Shao C, Khatri K, Leon D, McComb ME, Manfredsson FP, Sortwell CE, Zaia J. Glycomic and Proteomic Changes in Aging Brain Nigrostriatal Pathway. Mol Cell Proteomics 2018; 17:1778-1787. [PMID: 29915149 DOI: 10.1074/mcp.ra118.000680] [Citation(s) in RCA: 23] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/10/2018] [Revised: 06/12/2018] [Indexed: 12/19/2022] Open
Abstract
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.
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Zaia J, Bierbaum VM. Focus on Mass Spectrometry in Glycobiology and Related Fields, Honoring Catherine E. Costello, Recipient of the 2017 ASMS Award for a Distinguished Contribution in Mass Spectrometry. JOURNAL OF THE AMERICAN SOCIETY FOR MASS SPECTROMETRY 2018; 29:1061-1064. [PMID: 29855889 DOI: 10.1007/s13361-018-1957-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/08/2023]
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Wu J, Wei J, Hogan JD, Chopra P, Joshi A, Lu W, Klein J, Boons GJ, Lin C, Zaia J. Negative Electron Transfer Dissociation Sequencing of 3-O-Sulfation-Containing Heparan Sulfate Oligosaccharides. JOURNAL OF THE AMERICAN SOCIETY FOR MASS SPECTROMETRY 2018; 29:1262-1272. [PMID: 29564812 PMCID: PMC6004244 DOI: 10.1007/s13361-018-1907-0] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/23/2017] [Revised: 01/27/2018] [Accepted: 01/27/2018] [Indexed: 05/10/2023]
Abstract
Among dissociation methods, negative electron transfer dissociation (NETD) has been proven the most useful for glycosaminoglycan (GAG) sequencing because it produces informative fragmentation, a low degree of sulfate losses, high sensitivity, and translatability to multiple instrument types. The challenge, however, is to distinguish positional sulfation. In particular, NETD has been reported to fail to differentiate 4-O- versus 6-O-sulfation in chondroitin sulfate decasaccharide. This raised the concern of whether NETD is able to differentiate the rare 3-O-sulfation from predominant 6-O-sulfation in heparan sulfate (HS) oligosaccharides. Here, we report that NETD generates highly informative spectra that differentiate sites of O-sulfation on glucosamine residues, enabling structural characterizations of synthetic HS isomers containing 3-O-sulfation. Further, lyase-resistant 3-O-sulfated tetrasaccharides from natural sources were successfully sequenced. Notably, for all of the oligosaccharides in this study, the successful sequencing is based on NETD tandem mass spectra of commonly observed deprotonated precursor ions without derivatization or metal cation adduction, simplifying the experimental workflow and data interpretation. These results demonstrate the potential of NETD as a sensitive analytical tool for detailed, high-throughput structural analysis of highly sulfated GAGs. Graphical Abstract.
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Khatri K, Pu Y, Klein JA, Wei J, Costello CE, Lin C, Zaia J. Comparison of Collisional and Electron-Based Dissociation Modes for Middle-Down Analysis of Multiply Glycosylated Peptides. JOURNAL OF THE AMERICAN SOCIETY FOR MASS SPECTROMETRY 2018; 29:1075-1085. [PMID: 29663256 PMCID: PMC6004259 DOI: 10.1007/s13361-018-1909-y] [Citation(s) in RCA: 30] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/17/2017] [Revised: 01/09/2018] [Accepted: 01/29/2018] [Indexed: 05/12/2023]
Abstract
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.
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Wu ZL, Huang X, Ethen CM, Tatge T, Pasek M, Zaia J. Non-reducing end labeling of heparan sulfate via click chemistry and a high throughput ELISA assay for heparanase. Glycobiology 2018; 27:518-524. [PMID: 28025251 DOI: 10.1093/glycob/cww130] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/23/2016] [Accepted: 12/14/2016] [Indexed: 01/02/2023] Open
Abstract
Heparan sulfate (HS) is a linear polysaccharide found in the extracellular matrix (ECM) and on the cell membrane. It plays numerous roles in cellular events, including cell growth, migration and differentiation through binding to various growth factors, cytokines and other ECM proteins. Heparanase (HPSE) is an endoglycosidase that cleaves HS in the ECM and cell membrane. By degrading HS, HPSE not only alters the integrity of the ECM but also releases growth factors and angiogenic factors bound to HS chains, therefore, changes various cellular activities, including cell mobility that is critical for cancer metastasis. Accordingly, HPSE is an ideal drug target for cancer therapeutics. Here, we describe a method for non-reducing end labeling of HS via click chemistry (CC), and further use it in a novel HPSE assay. HS chains on a recombinant human syndecan-4 are first labeled at their non-reducing ends with GlcNAz using dimeric HS polymerase EXT1/EXT2. The labeled sample is then biotinylated through CC, immobilized on a multi-well plate and detected with ELISA. HPSE digestion of the biotinylated sample removes the label and, therefore, reduces the signal in ELISA assay. Non-reducing end labeling avoids the interference in an HPSE reaction caused by any internal labeling of HS. The assay is very sensitive with only 2.5 ng of labeled syndecan-4 needed in each reaction. The assay is also highly reproducible with a Z' > 0.6. Overall, this new method is suitable for high-throughput drug screening on HPSE.
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Klein JA, Meng L, Zaia J. Deep Sequencing of Complex Proteoglycans: A Novel Strategy for High Coverage and Site-specific Identification of Glycosaminoglycan-linked Peptides. Mol Cell Proteomics 2018; 17:1578-1590. [PMID: 29773674 DOI: 10.1074/mcp.ra118.000766] [Citation(s) in RCA: 37] [Impact Index Per Article: 6.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/28/2018] [Revised: 05/09/2018] [Indexed: 12/17/2022] Open
Abstract
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.
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van Eijk M, Rynkiewicz MJ, Khatri K, Leymarie N, Zaia J, White MR, Hartshorn KL, Cafarella TR, van Die I, Hessing M, Seaton BA, Haagsman HP. Lectin-mediated binding and sialoglycans of porcine surfactant protein D synergistically neutralize influenza A virus. J Biol Chem 2018; 293:10646-10662. [PMID: 29769321 DOI: 10.1074/jbc.ra117.001430] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2017] [Revised: 05/14/2018] [Indexed: 11/06/2022] Open
Abstract
Innate immunity is critical in the early containment of influenza A virus (IAV) infection, and surfactant protein D (SP-D) plays a crucial role in the pulmonary defense against IAV. In pigs, which are important intermediate hosts during the generation of pandemic IAVs, SP-D uses its unique carbohydrate recognition domain (CRD) to interact with IAV. An N-linked CRD glycosylation provides interactions with the sialic acid-binding site of IAV, and a tripeptide loop at the lectin-binding site facilitates enhanced interactions with IAV glycans. Here, to investigate both mechanisms of IAV neutralization in greater detail, we produced an N-glycosylated neck-CRD fragment of porcine SP-D (RpNCRD) in HEK293 cells. X-ray crystallography disclosed that the N-glycan did not alter the CRD backbone structure, including the lectin site conformation, but revealed a potential second nonlectin-binding site for glycans. IAV hemagglutination inhibition, IAV aggregation, and neutralization of IAV infection studies showed that RpNCRD, unlike the human analogue RhNCRD, exhibits potent neutralizing activity against pandemic A/Aichi/68 (H3N2), enabled by both porcine-specific structural features of its CRD. MS analysis revealed an N-glycan site-occupancy of >98% at Asn-303 of RpNCRD with complex-type, heterogeneously branched and predominantly α(2,3)-sialylated oligosaccharides. Glycan-binding array data characterized both RpNCRD and RhNCRD as mannose-type lectins. RpNCRD also bound LewisY structures, whereas RhNCRD bound polylactosamine-containing glycans. The presence of the N-glycan in the CRD increases the glycan-binding specificity of RpNCRD. These insights increase our understanding of porcine-specific innate defense against pandemic IAV and may inform the design of recombinant SP-D-based antiviral drugs.
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Hogan JD, Klein JA, Wu J, Chopra P, Boons GJ, Carvalho L, Lin C, Zaia J. Software for Peak Finding and Elemental Composition Assignment for Glycosaminoglycan Tandem Mass Spectra. Mol Cell Proteomics 2018; 17:1448-1456. [PMID: 29615495 DOI: 10.1074/mcp.ra118.000590] [Citation(s) in RCA: 20] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/06/2018] [Revised: 03/25/2018] [Indexed: 01/03/2023] Open
Abstract
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.
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Hu H, Khatri K, Zaia J. Algorithms and design strategies towards automated glycoproteomics analysis. MASS SPECTROMETRY REVIEWS 2017; 36:475-498. [PMID: 26728195 PMCID: PMC4931994 DOI: 10.1002/mas.21487] [Citation(s) in RCA: 71] [Impact Index Per Article: 10.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/10/2015] [Accepted: 11/30/2015] [Indexed: 05/09/2023]
Abstract
Glycoproteomics involves the study of glycosylation events on protein sequences ranging from purified proteins to whole proteome scales. Understanding these complex post-translational modification (PTM) events requires elucidation of the glycan moieties (monosaccharide sequences and glycosidic linkages between residues), protein sequences, as well as site-specific attachment of glycan moieties onto protein sequences, in a spatial and temporal manner in a variety of biological contexts. Compared with proteomics, bioinformatics for glycoproteomics is immature and many researchers still rely on tedious manual interpretation of glycoproteomics data. As sample preparation protocols and analysis techniques have matured, the number of publications on glycoproteomics and bioinformatics has increased substantially; however, the lack of consensus on tool development and code reuse limits the dissemination of bioinformatics tools because it requires significant effort to migrate a computational tool tailored for one method design to alternative methods. This review discusses algorithms and methods in glycoproteomics, and refers to the general proteomics field for potential solutions. It also introduces general strategies for tool integration and pipeline construction in order to better serve the glycoproteomics community. © 2016 Wiley Periodicals, Inc. Mass Spec Rev 36:475-498, 2017.
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