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Deciphering Protein Glycosylation by Computational Integration of On-chip Profiling, Glycan-array Data, and Mass Spectrometry*[S]

  • Zachary Klamer
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  • Peter Hsueh
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  • David Ayala-Talavera
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  • Brian Haab
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  • Author Footnotes
    * This research was supported by the National Cancer Institute (Early Detection Research Network, U01CA152653); the National Institute of General Medical Sciences (1R41GM112750); and the National Institute of Allergy and Infectious Disease (R21AI129872). The resources for the glycan analysis at the University of Georgia were supported in part by the National Institutes of Health (Research Resource for Biomedical Glycomics, P41GM10349010, and Orbitrap Fusion Tribrid Mass Spectrometer, 1S10OD018530, to Dr. Parastoo Azadi at the Complex Carbohydrate Research Center). The authors declare no competing interests.
    [S] This article contains supplemental material.
    1 The abbreviations used are:MSmass spectrometrygmapglycan modification and probingGalgalactoseGlcNAcN-acetyl-glucosamine.
Open AccessPublished:September 26, 2018DOI:https://doi.org/10.1074/mcp.RA118.000906
      The difficulty in uncovering detailed information about protein glycosylation stems from the complexity of glycans and the large amount of material needed for the experiments. Here we report a method that gives information on the isomeric variants of glycans in a format compatible with analyzing low-abundance proteins. On-chip glycan modification and probing (on-chip gmap) uses sequential and parallel rounds of exoglycosidase cleavage and lectin profiling of microspots of proteins, together with algorithms that incorporate glycan-array analyses and information from mass spectrometry, when available, to computationally interpret the data. In tests on control proteins with simple or complex glycosylation, on-chip gmap accurately characterized the relative proportions of core types and terminal features of glycans. Subterminal features (monosaccharides and linkages under a terminal monosaccharide) were accurately probed using a rationally designed sequence of lectin and exoglycosidase incubations. The integration of mass information further improved accuracy in each case. An alternative use of on-chip gmap was to complement the mass spectrometry analysis of detached glycans by specifying the isomers that comprise the glycans identified by mass spectrometry. On-chip gmap provides the potential for detailed studies of glycosylation in a format compatible with clinical specimens or other low-abundance sources.

      Graphical Abstract

      Obtaining detailed information about glycans on proteins is experimentally difficult. The difficulty in part stems from the complex nature of glycosylation. Because glycans are not simply linear polymers, as are proteins and nucleic acids, but can be branched at multiple points and have multiple options in the sequence of monosaccharides, the reducing-carbon linkage (3′, 4′, etc.), and anomeric type of linkage (alpha or beta), a given set of monosaccharides composing a glycan may have many possible isomers. Mass spectrometry (MS)

      The abbreviations used are:

      MS
      mass spectrometry
      gmap
      glycan modification and probing
      Gal
      galactose
      GlcNAc
      N-acetyl-glucosamine.
      is widely used to study glycans that are released from the protein backbone, and it readily provides information on the type and number of monosaccharides (
      • Thaysen-Andersen M.
      • Packer N.H.
      • Schulz B.L.
      Maturing glycoproteomics technologies provide unique structural insights into the n-glycoproteome and its regulation in health and disease.
      ), but the mass does not provide information about the branching, sequence, linkages, or anomeric state. The options are constrained according to allowed biosynthetic pathways, but even within the allowed options, many isomers can exist. Information about sequences and linkages can be acquired through additional methods such as MSn fragmentation (
      • Morelle W.
      • Michalski J.C.
      Analysis of protein glycosylation by mass spectrometry.
      ), chemical modifications (
      • Reiding K.R.
      • Blank D.
      • Kuijper D.M.
      • Deelder A.M.
      • Wuhrer M.
      High-throughput profiling of protein n-glycosylation by MALDI-TOF-MS employing linkage-specific sialic acid esterification.
      ), exoglycosidases digestions (
      • Morelle W.
      • Michalski J.C.
      Analysis of protein glycosylation by mass spectrometry.
      ), ion mobility separation (
      • Harvey D.J.
      • Seabright G.E.
      • Vasiljevic S.
      • Crispin M.
      • Struwe W.B.
      Isomer information from ion mobility separation of high-mannose glycan fragments.
      ), nuclear magnetic resonance imaging (
      • Wiegandt A.
      • Meyer B.
      Unambiguous characterization of n-glycans of monoclonal antibody cetuximab by integration of LC-MS/MS and (1)h NMR spectroscopy.
      ), or inferences based on biosynthetic pathways. Such methods require specialized tools, increased sample amounts, and expert knowledge. Integrating orthogonal data types can help resolve ambiguities from any single data source, yet the integrations are done manually and qualitatively; computational means of linking disparate data have not appeared.
      Another challenge is obtaining enough material for a detailed analysis. The sample requirements of the various MS-based approaches are being reduced regularly, but at present, sample amounts can be a problem when analyzing a protein from a clinical specimen or a model system with limited amounts of the protein available. To analyze the glycan structures of a purified protein, a common approach is detach the glycans, purify them, and analyze them by MS/MS. Such methods require 5–10 μg of a purified protein to acquire data on the masses and relative abundances of the glycans. With more sample and specialized methods, information can be obtained about the sequence, linkage, and anomeric variants of specific features (
      • Shajahan A.
      • Heiss C.
      • Ishihara M.
      • Azadi P.
      Glycomic and glycoproteomic analysis of glycoproteins-a tutorial.
      ,
      • Wada Y.
      • Dell A.
      • Haslam S.M.
      • Tissot B.
      • Canis K.
      • Azadi P.
      • Bäckström M.
      • Costello C.E.
      • Hansson G.C.
      • Hiki Y.
      • Ishihara M.
      • Ito H.
      • Kakehi K.
      • Karlsson N.
      • Hayes C.E.
      • Kato K.
      • Kawasaki N.
      • Khoo K.H.
      • Kobayashi K.
      • Kolarich D.
      • Kondo A.
      • Lebrilla C.
      • Nakano M.
      • Narimatsu H.
      • Novak J.
      • Novotny M.V.
      • Ohno E.
      • Packer N.H.
      • Palaima E.
      • Renfrow M.B.
      • Tajiri M.
      • Thomsson K.A.
      • Yagi H.
      • Yu S.Y.
      • Taniguchi N.
      Comparison of methods for profiling o-glycosylation: Human proteome organisation human disease glycomics/proteome initiative multi-institutional study of IgA1.
      ). A related approach is to proteolytically digest a purified protein and analyze the masses of the glycopeptides. Such a method is valuable for locating glycosites and quantifying relative site occupancies, but it is not as effective as detached glycan analysis for analyzing whole glycans. Glycopeptide analysis by MS can be quite sensitive, requiring only 100–200 ng of purified protein per injection, although obtaining enough for the digestions and purifications can be challenging in certain cases. A basic analysis of some features of glycosylation can be acquired using 1 μg or less of purified proteins. For example, lectin blotting of gel-separated prostate-specific antigen detected a specific glycoform using only 100 ng of protein (
      • Llop E.
      • Ferrer-Batallé M.
      • Barrabés S.
      • Guerrero P.E.
      • Ramírez M.
      • Saldova R.
      • Rudd P.M.
      • Aleixandre R.N.
      • Comet J.
      • de Llorens R.
      • Peracaula R.
      Improvement of prostate cancer diagnosis by detecting PSA glycosylation-specific changes.
      ), and in situ glycan release and analysis by MALDI MS could be compatible with similarly low protein quantities (
      • Powers T.W.
      • Neely B.A.
      • Shao Y.
      • Tang H.
      • Troyer D.A.
      • Mehta A.S.
      • Haab B.B.
      • Drake R.R.
      MALDI imaging mass spectrometry profiling of n-glycans in formalin-fixed paraffin embedded clinical tissue blocks and tissue microarrays.
      ). Thorough analyses of the sequences, branching, linkages, and anomeric states of protein glycosylation are typically limited to biopharmaceutical applications where material can be obtained in high abundance or from recombinant production, as in a study of erythropoietin (
      • Yang Y.
      • Liu F.
      • Franc V.
      • Halim L.A.
      • Schellekens H.
      • Heck A.J.
      Hybrid mass spectrometry approaches in glycoprotein analysis and their usage in scoring biosimilarity.
      ). Additional methods to complement the existing toolbox of glycan-analysis methods would be useful, especially if they could provide increased information about sequences, branching, linkages, and anomeric states, while being compatible with application to clinical specimens.
      We previously introduced an on-chip method that can provide information about the glycosylation of proteins using a small amount of input material (
      • Reatini B.S.
      • Ensink E.
      • Liau B.
      • Sinha J.Y.
      • Powers T.W.
      • Partyka K.
      • Bern M.
      • Brand R.E.
      • Rudd P.M.
      • Kletter D.
      • Drake R.
      • Haab B.B.
      Characterizing protein glycosylation through on-chip glycan modification and probing.
      ). The method, called on-chip glycan modification and probing (on-chip gmap), involves the on-chip capture of proteins out of clinical samples or the direct printing of a purified protein, the repeated modification of the glycans using exoglycosidases, and the probing of the resulting glycans using panels of lectins. The method is analogous to conventional glycan sequencing by the parallel or sequential application of exoglycosidases and analysis by electrophoresis (
      • Tarentino A.L.
      • Trimble R.B.
      • Plummer Jr., T.H.
      Enzymatic approaches for studying the structure, synthesis, and processing of glycoproteins.
      ), but it analyzes the cleaved glycans by lectin profiling rather than mobility shifts. We demonstrated that the method can help to meet the need of increased information about isomeric variants while having low sample requirements.
      The previous work demonstrated the feasibility of the approach, but it also revealed areas that needed development. The analysis algorithms were built around solving for glycan motifs, or patterns of substructures, rather than complete glycans. This method left uncertainty in the arrangements of the motifs with respect to each other and uncertainty in which motifs were part of the same glycan. As a result, the method also left uncertainty about the heterogeneity in glycosylation that is present on nearly every glycoprotein because information was not given about whether the individual motifs comprised few or many glycans. Furthermore, based on the potential for improved accuracy by integrating orthogonal data types, we needed a way to computationally integrate the on-chip-gmap data with analyses from glycan arrays, which give details about lectin and exoglycosidases specificity, and from MS experiments, which provide the monosaccharide compositions of the glycans.
      In this work, we developed an algorithm to process data from on-chip gmap in a way that addresses the above limitations: It interprets the heterogeneity and relative abundances of glycans in a sample, and it computationally integrates information from glycan-array and MS experiments. To test the system, we analyzed glycoproteins for which detailed information on glycosylation was obtainable, meaning that they could be acquired in high abundance. For working out the method, we printed microspots of proteins directly on the slide, as opposed to capturing the proteins out of solution using microspots of an antibody (
      • Reatini B.S.
      • Ensink E.
      • Liau B.
      • Sinha J.Y.
      • Powers T.W.
      • Partyka K.
      • Bern M.
      • Brand R.E.
      • Rudd P.M.
      • Kletter D.
      • Drake R.
      • Haab B.B.
      Characterizing protein glycosylation through on-chip glycan modification and probing.
      ). We compared the independently determined information with results from on-chip gmap, either alone or in combination with MS. We show that on-chip gmap provides accurate information about glycosylation and that the integration of basic mass information provides further improved accuracy. In addition, we show that on-chip gmap promises to be valuable for assisting the interpretation of MS data, in particular by specifying the isomers that comprise each glycan.

      DISCUSSION

      The on-chip gmap method takes advantage of the specificities of glycosidases and lectins, combined with glycan-array data and computational tools for integrating the information, to produce an approach for thoroughly investigating isomeric variants of glycans. As such, it could fill a valuable role in the analysis of protein glycosylation. Furthermore, it could reduce the amount of protein needed to get information about isomeric variants of glycans. Here, the method consumed just 120 ng of protein to get accurate information about the glycan isomers on fetuin and transferrin. More was used to create the arrays–about 16.6 μg in solution, in this embodiment–but most could be recovered for later use, and the amount could be lowered in various ways. One could use printing from just one pin, for example, or an ink-jet type of spotter that requires less material. Alternatively, if one has appropriate antibodies, the antibodies could be printed on the arrays and used to capture proteins out of solution. The incubation of a 1 μg/ml solution would typically saturate binding. Thus, based on the use of about 30–50 μl of solution, the protein requirement would be just 30–50 ng. But even if prepurification and direct spotting of the protein is necessary, the sample needs are favorable when contrasted with other approaches for probing isomeric variants. For example, an NMR study of glycoforms of cetuximab used about 2.5 mg of protein to assign isomers for the 10 most abundant structures (
      • Wiegandt A.
      • Meyer B.
      Unambiguous characterization of n-glycans of monoclonal antibody cetuximab by integration of LC-MS/MS and (1)h NMR spectroscopy.
      ); a previous study of the glycosylation of mucins purified from human serum required about 5 ml (
      • Storr S.J.
      • Royle L.
      • Chapman C.J.
      • Hamid U.M.
      • Robertson J.F.
      • Murray A.
      • Dwek R.A.
      • Rudd P.M.
      The o-linked glycosylation of secretory/shed muc1 from an advanced breast cancer patient's serum.
      ); the analysis presented here of detached N-glycans by MS/MS and fragmentation by MSn used ∼300 μg of protein; and the analysis presented here by capillary electrophoresis used ∼50 μg of protein.
      On-chip gmap method could be used in combination with other approaches for increased value. Clearly, the most useful combinations will be with MS analyses, owing to the complementary advantages and limitations of each method. Detached-glycan analysis provides the masses of intact glycans, but it provides no information on site occupancy and limited information on isomeric variants; on-chip gmap provides linkages and sequences but not masses or site occupancies, and glycopeptide analysis provides information on the attachment sites of the glycans on the protein backbone but presents challenges in identifying masses of complete, intact glycans and in finding all glycopeptides. For example, a study of the protein erythropoietin characterized site-specific heterogeneity in glycans but without assignments of linkages (
      • Yang Y.
      • Liu F.
      • Franc V.
      • Halim L.A.
      • Schellekens H.
      • Heck A.J.
      Hybrid mass spectrometry approaches in glycoprotein analysis and their usage in scoring biosimilarity.
      ) and a study of glycoforms of monoclonal antibodies likewise did not make assignments of isomers (
      • Liu S.
      • Gao W.
      • Wang Y.
      • He Z.
      • Feng X.
      • Liu B.F.
      • Liu X.
      Comprehensive n-glycan profiling of cetuximab biosimilar candidate by NP-HPLC and MALDI-MS.
      ). Therefore, the MS methods could be coupled to on-chip gmap to provide deeper information than possible by any single method. A practical strategy for accomplishing such experiments could be enriching proteins out of biological solutions using antibody arrays (
      • Reatini B.S.
      • Ensink E.
      • Liau B.
      • Sinha J.Y.
      • Powers T.W.
      • Partyka K.
      • Bern M.
      • Brand R.E.
      • Rudd P.M.
      • Kletter D.
      • Drake R.
      • Haab B.B.
      Characterizing protein glycosylation through on-chip glycan modification and probing.
      ,
      • Haab B.B.
      • Dunham M.J.
      • Brown P.O.
      Protein microarrays for highly parallel detection and quantitation of specific proteins and antibodies in complex solutions.
      ), which may be compatible with both on-chip gmap and MALDI. The value of linking orthogonal methods has been appreciated previously, as in the use of antibody and lectin binding to interpret MALDI data (
      • Palma A.S.
      • Liu Y.
      • Zhang H.
      • Zhang Y.
      • McCleary B.V.
      • Yu G.
      • Huang Q.
      • Guidolin L.S.
      • Ciocchini A.E.
      • Torosantucci A.
      • Wang D.
      • Carvalho A.L.
      • Fontes C.M.
      • Mulloy B.
      • Childs R.A.
      • Feizi T.
      • Chai W.
      Unravelling glucan recognition systems by glycome microarrays using the designer approach and mass spectrometry.
      ) or in the combined use of NMR and MS (
      • Fellenberg M.
      • Behnken H.N.
      • Nagel T.
      • Wiegandt A.
      • Baerenfaenger M.
      • Meyer B.
      Glycan analysis: Scope and limitations of different techniques–A case for integrated use of LC-MS(/MS) and NMR techniques.
      ), but automated algorithms to combine the methods were not available. The computational tools presented here may facilitate the linking of the data and the integration of additional, disparate technologies such as lectin arrays (
      • Pilobello K.T.
      • Krishnamoorthy L.
      • Slawek D.
      • Mahal L.K.
      Development of a lectin microarray for the rapid analysis of protein glycopatterns.
      ).
      A limitation of on-chip gmap is its diminishing value for proteins with high heterogeneity or many similar glycans. The current method accounts for heterogeneity by deconvolving the signals from individual glycans, but the challenge gets more difficult as the glycoprotein becomes more complex. We show that, fundamentally, the method works, and that by increasing the experimental depth–more lectins and more rounds of enzymatic treatment–we get closer to the right answer even for a highly complex protein like fetuin. But for proper application, we must have output metrics that indicate the confidence of the findings and design algorithms to optimize the sequences of lectins and enzymes that probe specific glycans. The use of reference material that has been well characterized could help to clarify the limitations of complexity that are accessible with particular experiments and serve as a means of consistent calibration. In addition, heterogeneity could be addressed by fractionating glycoforms or domains prior to analysis.
      A goal for further development is to increase the choices of lectins and enzymes. Many glycosidases and lectins already are available, and more are continually being discovered or developed. Not all of them function well for in vitro analyses, but it is likely that experimental optimization and protein engineering can improve activities in many cases. For example, researchers engineered a ricin-type lectin from earthworm to have high affinity to α2–6 sialic acid (
      • Yabe R.
      • Itakura Y.
      • Nakamura-Tsuruta S.
      • Iwaki J.
      • Kuno A.
      • Hirabayashi J.
      Engineering a versatile tandem repeat-type alpha2–6sialic acid-binding lectin.
      ) and used directed evolution to produce specificity for 6-sulfated galactose (
      • Hu D.
      • Tateno H.
      • Kuno A.
      • Yabe R.
      • Hirabayashi J.
      Directed evolution of lectins with sugar-binding specificity for 6-sulfo-galactose.
      ). Another group created deletion mutants of the yeast peptide:N-glycanase enzyme to enhance deglycosylation activity (
      • Wang S.
      • Xin F.
      • Liu X.
      • Wang Y.
      • An Z.
      • Qi Q.
      • Wang P.G.
      N-terminal deletion of peptide:N-glycanase results in enhanced deglycosylation activity.
      ). Anti-glycan antibodies are a good alternative and are being produced in increasing quantities (
      • Sterner E.
      • Flanagan N.
      • Gildersleeve J.C.
      Perspectives on anti-glycan antibodies gleaned from development of a community resource database.
      ), including antibodies generated from lamprey (
      • Collins B.C.
      • Gunn R.J.
      • McKitrick T.R.
      • Cummings R.D.
      • Cooper M.D.
      • Herrin B.R.
      • Wilson I.A.
      Structural insights into VLR fine specificity for blood group carbohydrates.
      ).
      Another important goal for development is to increase the accuracy of the information about specificities. Glycan arrays facilitate detailed analyses of lectin specificity (
      • Rillahan C.D.
      • Paulson J.C.
      Glycan microarrays for decoding the glycome.
      ), and we recently developed their use for analyzing glycosidase specificity (
      • Klamer Z.
      • Staal B.
      • Prudden A.R.
      • Liu L.
      • Smith D.F.
      • Boons G.J.
      • Haab B.B.
      Mining high-complexity motifs in glycans: A new language to uncover the fine-specificities of lectins and glycosidases.
      ). The optimal use of glycan arrays will involve custom-produced arrays designed to probe specific areas of fine specificity. Researchers are increasingly creating arrays with specialized content, such as glucans that were purified from natural sources (
      • Palma A.S.
      • Liu Y.
      • Zhang H.
      • Zhang Y.
      • McCleary B.V.
      • Yu G.
      • Huang Q.
      • Guidolin L.S.
      • Ciocchini A.E.
      • Torosantucci A.
      • Wang D.
      • Carvalho A.L.
      • Fontes C.M.
      • Mulloy B.
      • Childs R.A.
      • Feizi T.
      • Chai W.
      Unravelling glucan recognition systems by glycome microarrays using the designer approach and mass spectrometry.
      ), human milk oligosaccharides (
      • Prudden A.R.
      • Liu L.
      • Capicciotti C.J.
      • Wolfert M.A.
      • Wang S.
      • Gao Z.
      • Meng L.
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      • Boons G.J.
      Synthesis of asymmetrical multiantennary human milk oligosaccharides.
      ), microbial glycans (
      • Stowell S.R.
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      • Berger O.
      • Razi N.
      • Heimburg-Molinaro J.
      • Rodrigues L.C.
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      • Noll A.J.
      • von Gunten S.
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      • Knirel Y.A.
      • Paulson J.C.
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      Microbial glycan microarrays define key features of host-microbial interactions.
      ,
      • Wang D.
      • Liu S.
      • Trummer B.J.
      • Deng C.
      • Wang A.
      Carbohydrate microarrays for the recognition of cross-reactive molecular markers of microbes and host cells.
      ), and various types of sialylated structures (
      • Nycholat C.M.
      • McBride R.
      • Ekiert D.C.
      • Xu R.
      • Rangarajan J.
      • Peng W.
      • Razi N.
      • Gilbert M.
      • Wakarchuk W.
      • Wilson I.A.
      • Paulson J.C.
      Recognition of sialylated poly-n-acetyllactosamine chains on N- and O-linked glycans by human and avian influenza a virus hemagglutinins.
      ,
      • Song X.
      • Yu H.
      • Chen X.
      • Lasanajak Y.
      • Tappert M.M.
      • Air G.M.
      • Tiwari V.K.
      • Cao H.
      • Chokhawala H.A.
      • Zheng H.
      • Cummings R.D.
      • Smith D.F.
      A sialylated glycan microarray reveals novel interactions of modified sialic acids with proteins and viruses.
      ,
      • Padler-Karavani V.
      • Song X.
      • Yu H.
      • Hurtado-Ziola N.
      • Huang S.
      • Muthana S.
      • Chokhawala H.A.
      • Cheng J.
      • Verhagen A.
      • Langereis M.A.
      • Kleene R.
      • Schachner M.
      • de Groot R.J.
      • Lasanajak Y.
      • Matsuda H.
      • Schwab R.
      • Chen X.
      • Smith D.F.
      • Cummings R.D.
      • Varki A.
      Cross-comparison of protein recognition of sialic acid diversity on two novel sialoglycan microarrays.
      ). Bead-based arrays may be particularly useful for rapid customization (
      • Purohit S.
      • Li T.
      • Guan W.
      • Song X.
      • Song J.
      • Tian Y.
      • Li L.
      • Sharma A.
      • Dun B.
      • Mysona D.
      • Ghamande S.
      • Rungruang B.
      • Cummings R.D.
      • Wang P.G.
      • She J.X.
      Multiplex glycan bead array for high throughput and high content analyses of glycan binding proteins.
      ). In addition, new synthetic methods are enabling the production of structures that were previously difficult to synthesize, such as asymmetrically branched N-glycans (
      • Wang Z.
      • Chinoy Z.S.
      • Ambre S.G.
      • Peng W.
      • McBride R.
      • de Vries R.P.
      • Glushka J.
      • Paulson J.C.
      • Boons G.J.
      A general strategy for the chemoenzymatic synthesis of asymmetrically branched n-glycans.
      ,
      • Wu Z.
      • Liu Y.
      • Li L.
      • Wan X.F.
      • Zhu H.
      • Guo Y.
      • Wei M.
      • Guan W.
      • Wang P.G.
      Decoding glycan protein interactions by a new class of asymmetric n-glycans.
      ), which could reveal unusual fine specificities in lectins or glycosidases (
      • Klamer Z.
      • Staal B.
      • Prudden A.R.
      • Liu L.
      • Smith D.F.
      • Boons G.J.
      • Haab B.B.
      Mining high-complexity motifs in glycans: A new language to uncover the fine-specificities of lectins and glycosidases.
      ). Integrating glycan-array analyses with lectin structural information (
      • Grant O.C.
      • Tessier M.B.
      • Meche L.
      • Mahal L.K.
      • Foley B.L.
      • Woods R.J.
      Combining 3d structure with glycan array data provides insight into the origin of glycan specificity.
      ) also promises to increase precision in charactering specificities.
      In conclusion, on-chip gmap with the integration of orthogonal data provides high-accuracy analyses of protein glycosylation, and it opens the door to detailed studies of glycosylation using small amounts of protein, such as would be available from clinical specimens. The direct analysis of the clinical specimens from patients could foster the discovery of glycoforms that are associated with disease. Once a glycan is discovered, a robust, highly reproducible assay could be developed that would be suitable for diagnostics. Furthermore, if researchers have the ability to thoroughly study protein glycosylation using tiny amounts of protein, they may be able to obtain new information about the features of glycans that affect biological mechanisms.

      DATA AVAILABILITY

      The full raw data from the nanospray ionization-MS for the full glycan analysis and LTQ linear ion trap MS, including MSn fragmentation for the sialic-acid linkage analysis, are available in the Supplemental Data.

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