• We are sorry, but NCBI web applications do not support your browser and may not function properly. More information
Logo of nihpaAbout Author manuscriptsSubmit a manuscriptNIH Public Access; Author Manuscript; Accepted for publication in peer reviewed journal;
Cell. Author manuscript; available in PMC Nov 24, 2011.
Published in final edited form as:
PMCID: PMC3008369
NIHMSID: NIHMS253688

Glycomics Hits the Big Time

Abstract

Cells run on carbohydrates. Glycans, sequences of carbohydrates conjugated to proteins and lipids, are arguably the most abundant and structurally diverse class of molecules in nature. Recent advances in glycomics reveal the scope and scale of their functional roles and their impact on human disease.

By analogy to the genome, transcriptome, or proteome, the ‘glycome’ is the complete set of glycans and glycoconjugates that are made by a cell or organism under specific conditions. Therefore, ‘glycomics’ refers to studies that attempt to define or quantify the glycome of a cell, tissue or organism (Bertozzi and Sasisekharan, 2009). In eukaryotes, protein glycosylation generally involves the covalent attachment of glycans to either serine, threonine or asparagine residues. Glycoproteins occur in all cellular compartments. Glycans are also attached to lipids, often ceramide, which is comprised of sphingosine, a hydrocarbon amino alcohol and a fatty acid. Complex glycans are mainly attached to secreted or cell surface proteins and they do not cycle on and off of the polypeptide. In contrast, the monosaccharide O-linked N-acetylglucosamine (O-GlcNAc) cycles rapidly on serine or threonine residues of many nuclear and cytoplasmic proteins. Identifying the number, structure and function of glycans in cellular biology is a daunting task, but one that's been made easier in recent years by advances in technology and by our growing appreciation of how integral glycans are to biology (Varki et al., 2009).

The scope of the glycomics challenge is immense. The covalent addition of glycans to proteins and lipids represents not only the most abundant post-translational modification (PTM), but also by far the most structurally diverse. Although it is commonly stated that over fifty-percent of all polypeptides are covalently modified by glycans (Apweiler et al., 1999), even this estimate is far too low, since it fails to include that myriad nuclear and cytoplasmic proteins are modified by O-GlcNAc (Hart et al., 2007). Even though the generic term, ‘glycosylation’ is often used to categorize and lump all glycan modifications of proteins into one bin, side-by-side with other post-translational modifications, such as phosphorylation, acetylation, ubiquitination, or methylation, such a view is not only inaccurate, but also is completely misleading. If one only considers the linkage of the first glycan to the polypeptide in both prokaryotic and eukaryotic organisms, there are at least thirteen different monosaccharides and eight different amino acids involved in glycoprotein linkages, with a total of at least forty-one different chemical bonds known to be linking the glycan to the protein (Spiro, 2002). Importantly, each one of these unique glycan:protein linkages is surely as different both in structure and function as protein methylation is from acetylation.

Of course, this modification is not only about a single linkage. When structural diversity of the additional oligosaccharide branches of glycans and the added diversity of complex terminal saccharides on glycans, such as fucose or sialic acids (about fifty different sialic acids are known (Schauer, 2009)), are taken into account, the molecular diversity and varied functions of protein-bound glycans rapidly increase exponentially. Just the ‘sialome’ (Cohen and Varki, 2010) rivals or exceeds many other post-translational modifications in abundance and structural/functional diversity. In addition, chemical modifications, such as phosphorylation, sulfation and acetylation increase the glycan structural/functional diversity even more. Thus, categorizing ‘glycosylation’ as a single type of post-translational modification is neither useful nor at all reflective of reality.

Dynamic Structural Complexity Underlies Glycan Functions

Glyconjugates provide dynamic structural diversity to proteins and lipids that is responsive to cellular phenotype, metabolic state and to the developmental stage of cells. Complex glycans play critical roles in intercellular and intracellular processes, which are fundamentally important to the development of multicellularity (Figure 1). Unlike nucleic acids and proteins, glycan structures are not hardwired into the genome, depending upon a template for their synthesis. Rather the glycan structures that end up on a polypeptide or lipid result from the concerted actions of highly-specific glycosyltransferases (Lairson et al., 2008), which in-turn are dependent upon the concentrations and localization of high-energy nucleotide sugar donors, such as UDP-N-acetylglucosamine, the endpoint of the hexosamine biosynthetic pathway. Therefore, the glycoforms of a glycoprotein depend upon many factors directly tied to both gene expression and cellular metabolism.

Figure 1
Glycans permeate cellular biology

There are at-least two hundred and fifty glycosyltransferases in the human genome, and it has been estimated that about two-percent of the human genome encodes proteins involved in glycan biosynthesis, degradation or transport (Schachter and Freeze, 2009). Biosynthesis of the nucleotide sugar donors is directly regulated by nucleic acid, glucose and energy metabolism, and the compartmentalization of these nucleotide sugar donors is highly regulated by specific transporters. Protein glycosylation is therefore controlled by rates of polypeptide translation and protein folding, localization of and competition between glycosyltransferases, cellular concentration and localization of nucleotide sugars, the localization of glycosidases, and by membrane trafficking. Thus, individual glycosylation sites on the same polypeptide can contain different glycan structures that reflect both the type and status of the cell in which they are synthesized. For example, the glycoforms of the membrane protein Thy-1, are very different in lymphocytes than they are in brain, despite having the same polypeptide sequence (Rudd and Dwek, 1997). Conversely, even small changes in polypeptide sequence or structure will alter the types of glycan structures attached to a polypeptide. For example, histocompatiblility antigen polypeptides with over ninety-percent sequence homology contain different N-linked glycan profiles at individual sites, reflective of their allelic type, even when they are synthesized within the same cells (Swiedler et al., 1985). Thus, site-specific protein glycosylation is highly regulated by gene expression of glycan processing enzymes, by polypeptide structure at all levels, and by cellular metabolism.

Technology of Glycomics

A detailed understanding of cellular processes will require a detailed appreciation of the glycans modulating proteins and pathways. Although this ultimate goal of glycomics is laudable, we are a very long way from having the technology to completely characterize the glycome of even a simple cell or tissue. Not only is the glycome much more complex than the genome, transcriptome or proteome, as noted above, it is also much more dynamic, varying considerably not only with cell type but also with the developmental stage and metabolic state of a cell. Even very conservative estimates indicate that there are well over a million different glycan structures in a mammalian cell's glycome. However, upon considering ‘functional glycomics’, it is estimated that the binding sites of glycan binding proteins (GBPs), such as antibodies, lectins, receptors, toxins, microbial adhesions or enzymes (Figure 1) can accommodate only up to two to six monosaccharides within a glycan structure (Cummings, 2009). Therefore, the number of specific glycan sub-structures that bind to biologically important GBPs in a cell may be fewer than ten thousand, a number within the realm of current analytical and, if targeted, chemical or enzymatic synthetic capabilities.

Until recently, the lack of tools and the inherent complexity of glycans have been major barriers preventing most biologists from embracing the importance of glycans in biology. Recent technological advances have significantly lowered these barriers. Indeed, the tools of glycomics, and the subfields of glycoproteomics, glycolipidomics and proteoglycomics have all progressed substantially in recent years (Krishnamoorthy and Mahal, 2009; Laremore et al., 2010). Major technological advances, many of which are shared with proteomics, have recently allowed semi-quantitative profiling of glycans and glycoproteins (Krishnamoorthy and Mahal, 2009; Vanderschaeghe et al., 2010). Some of these advances are the result of the National Institute of General Medical Science's (NIGMS) support of the Consortium for Functional Glycomics (CFG), which has served to focus and assist over five hundred researchers on issues related to glycomics (Paulson et al., 2006; Raman et al., 2006).

Kobata and colleagues were amongst the first to profile N-glycans, well before the current concepts of ‘glycomics’ were conceived. Despite the lack of many modern methods, their pioneering work was characterized by a high level of rigor in defining the arrays of N-glycan structures present in cells, tissues and on specific proteins (Endo, 2010). Currently, a wide variety of high-resolution and highly sensitive methods are available, including capillary electrophoresis (CE), high performance liquid chromatography (HPLC) and lectin microarrays.

Glycans are often profiled after their release from polypeptides, which results in the loss of any information about proteins and sites to which they were attached. Even though it is much more difficult, it is also much preferable to perform glycopeptide profiling (glycoproteomics) to first identify attachment sites prior to detailed profiling or structural analysis of the glycans present on a polypeptide. The ultimate goal of glycoproteomics, which is to define all of the molecular species (glycoforms) of glycoproteins in a cell or tissue, has not yet been realized for any glycoprotein with more than one glycan attachment site. N-glycans are generally released from proteins by peptide-N-glycosidase F (PNGase F), which cleaves most, but not all N-glycans. Unfortunately, no such broadly specific enzyme exists for O-glycans, which are generally released by chemical methods, such as alkali-induced β-elimination or by hydrazinolysis. However, for relatively pure glycoproteins, so called ‘top-down’ mass spectrometric methods, which do not involve prior release of the glycans, may eventually prove useful, as instrumentation and methods improve (Reid et al., 2002).

Due to the small sample sizes involved, most CE or HPLC separation methods require chemical modification of released glycans with fluorescent compounds. CE and HPLC methods provide high-resolution separation of glycans, and when combined with laser induced fluorescent detection (LIF), tagged-glycans can be detected in the low femtomole range. High pH anion-exchange chromatography (HPAEC) with pulsed-amperiometric detection separates glycans with high resolution and detects them with high sensitivity without chemical modification, but the high alkalinity employed can be problematic for some labile structures.

Lectins, which are defined as carbohydrate binding proteins that are neither antibodies nor enzymes, have a wide range of glycan binding specificities, suitable for partial characterization of a glycome. Lectin microarrays use methods and equipment similar to that employed for nucleic acid arrays. Given the large number of different lectins available, lectin microarrays can provide information about the glycome in a high-throughput fashion, which is particularly useful in profiling glycans produced by infectious organisms (Hsu et al., 2006). In the future, it is highly likely that glycomics will play a central role in combating infectious disease. However, many technical issues remain to be resolved, such as standardization required for clinical use, the development of purified recombinant lectins, and better definition of the specificities of many lectins (Gupta et al., 2010).

Both matrix-assisted laser desorption ionization (MALDI) and electrospray mass spectrometry have played a key role in glycan profiling and in glycoproteomics (An et al., 2009; North et al., 2010; Zaia, 2010). For biomarker discovery, affinity enrichment approaches, based upon chemical modification and solid-phase extraction of N-linked glycoproteins, have proven useful in profiling N-linked glycoprotein sites from serum or even from paraffin embedded tissues (Tian et al., 2009). Recently, using lectin binding, combined with advanced mass spectrometric methods, thousands of N-glycan attachment sites have been mapped, a prerequisite for understanding their functions (Zielinska et al., 2010).

Given the structural diversity of glycans, all of these glycomic approaches generate vast amounts of data. Glycan bioinformatics has made great strides within recent years with major efforts from several laboratories (Aoki-Kinoshita, 2008). At least four major publicly available carbohydrate databases (Glycosciences.de, KEGG GLYCAN, EurocarbDB and CFG) are now maintained, and efforts to structure them in a uniform format have been in progress for quite some time. In addition, the Carbohydrate-Active EnZyme database, (CAZy) has played a key role in providing a global understanding of carbohydrate active enzymes, documenting their evolutionary relationships, providing a framework for elucidating common mechanisms, and for establishing the relationship between glycogenomics and glycomes expressed by cells (Cantarel et al., 2009). Moreover, recent advances in bioinformatic analysis tools for complex glycomic mass spectrometry data sets have allowed complex data to be presented in formats useful to non-experts in all fields of biology (Ceroni et al., 2008; Goldberg et al., 2005)

Perhaps one of the most important contributions to the field of functional glycomics has been the development of well-defined glycan microarrays, which currently display over five-hundred different glycan structures (Smith et al., 2010). The NIGMS supported Consortium for Functional Glycomics (CFG) has generated and made publicly available custom-made DNA microarrays that represent glycosyltransferases and glycan binding proteins. The CFG also has developed databases that present phenotypic and biochemical data on glycosyltransferase knock-out mice. Even though knocking out a single glycosyltransferase gene often affects hundreds of glycoconjugates and myriad biological processes, these mutant mice have proven valuable in revealing the fundamental biological importance of glycans. The microarrays and the databases produced by the CFG member community at-large are publically available on the CFG web site (http://www.functionalglycomics.org), and have resulted in a profound increase in our understanding of the binding specificities of GBPs, including lectins key to inflammation and immunity, and on infectious microbes or viruses. However, a major barrier preventing glycan biology from being incorporated more into the mainstream is the continued failure by the community to adopt a universally standard glycan structural format and database that are easily accessed worldwide. Most importantly, glycan databases must eventually be incorporated into standard interactive databases that are supported by public agencies (such as NCBI or EMBL) before glycan biology can be fully integrated into the wider research community.

From Glycomics to Biology

Glycans are directly involved in almost every biological process and certainly play a major role in nearly every human disease (Figure 1). Genetic studies in tissue culture cells indicate that specific complex glycan structures are generally not essential to a cell growing in culture, indicating that most of the functions of complex glycans are at the multicellular level. In contrast, the cycling monosaccharide, O-GlcNAc, on nuclear and cytoplasmic proteins, is essential even at the single cell level in mammals (Hart et al., 2007).

The critical roles of glycans in mammals are now well established not only by the dearth of mutations in glycan biosynthetic enzymes that survive development, but also by the severe phenotypes generated when such mutations are not lethal. These severe phenotypes are clearly illustrated by the congenital disorders of glycosylation (CDGs) (Schachter and Freeze, 2009), which are associated with severe mental and developmental abnormalities. Also, the severe muscular dystrophy that results from defective O-glycosylation of α-dystroglycan (Yoshida-Moriguchi et al., 2010), further illustrates how a mutation in a glycan biosynthetic enzyme results in a devastating disease. The interplay between O-GlcNAcylation and phosphorylation on nuclear and cytoplasmic proteins plays a key role in the etiology of diabetes, neurodegenerative disease and cancer (Hart et al., 2007; Zeidan and Hart, 2010).

It has long been appreciated that alterations in cell surface glycans contribute to the metastastatic and neoplastic properties of tumor cells (Taniguchi, 2008). The functions of many receptors are modulated by their glycans such as modulation of Notch receptors by the action of specific glycosyltransferases (Moloney et al., 2000), which regulate Notch's activation by its ligands, affecting many developmental events. Selectins, which specifically bind to a subset of fucosylated and sialylated glycans, play a critical role in leukocyte homing to sites of inflammation. Indeed, a selectin inhibitor is currently in phase 2 clinical trials for vaso-occlusive sickle cell disease (Chang et al., 2010). Siglecs, which are a family of cell surface sialic acid binding lectins, play a fundamental role in regulating lymphocyte functions and activation. Recent studies on galectins, a family of β-galactoside binding lectins, have shown that they play a critical role in the organization of receptors on the cell surface, and play important roles in immunity, infections, development and inflammation (Lajoie et al., 2009). Proteoglycans and glycosaminoglycans play a key role in regulation of growth factors, in microbial binding, in tissue morphogenesis and in the etiology of cardiovascular disease. Proteoglycans are perhaps the most complicated and information rich molecules in biology, and progress in proteoglycomics has begun to accelerate (Ly et al., 2010). Nearly all microbes and viruses that infect humans bind to cells by attaching to specific cell surface glycans. Glycomics and glycan arrays will have a substantial impact upon future research toward both diagnosing and preventing infectious disease.

Some of the most important drugs on the market are already the result of glycomics. The anti-flu virus drugs, Relenza™ and Tamiflu™ are structural analogs of sialic acids that inhibit the flu virus neuraminidase and the transmission of the virus. Natural heparin, a sulfated glycosaminoglycan, and chemically defined synthetic heparin oligosaccharides, have long been widely used in the clinic as anticoagulants and for many other clinical uses. Hyaluronic acid, a non-sulfated glycosaminoglycan, is used in the treatment of arthritis. Many recombinant pharmaceuticals, including therapeutic monoclonal antibodies, are glycoproteins, and their specific glycoforms are key to their bio-activity and half lives in circulation, and to their possible induction of deleterious immune responses when they do not contain the correct glycans. Given this landscape, the pharmaceutical industry and the US Food and Drug Administration are rapidly realizing the critical importance, both in terms of bioactivity and safety, of carefully defining the glycoforms of any therapeutics derived from glycoconjugates.

Glycoproteomics, Glycolipidomics and Biomarkers

Clinical cancer diagnostic markers are often glycoproteins, but most current diagnostic tests only measure the expression of the polypeptide. Clearly, given the long known alterations in glycans associated with cancer, it is highly likely that cancer markers that detect specific glycoforms of a protein will have much higher sensitivity and specificity for early detection of cancer (Packer et al., 2008; Taniguchi, 2008). Thus, the convergence of glycomics and glycoproteomics is key to the discovery of biomarkers for the early detection of cancer (Taylor et al., 2009). Recently, the Food and Drug Administration has approved fucosylated α-fetoprotein as a diagnostic marker of primary hepatocarcinoma. In addition, fucosylated haptoglobin may be a much better marker of pancreatic cancer than simply monitoring the expression of the haptoglobin polypeptide. Indeed, The National Cancer Institute has begun an initiative to discover, develop and clinically validate glycan biomarkers for cancer (http://glycomics.cancer.gov/). System biology analyses of the glycome to identify biomarkers of human disease will by necessity also employ many of the same methods used by genomics, proteomics, metabolomics and lipidomics (Figure 2) (Packer et al., 2008). Due to the critical roles of glycans in cardiovascular disease, lung disease and in the functions of blood cells, the National Heart Lung and Blood Institute (NHLBI) has recognized an acute need to train more researchers in the area of glycosciences by creating a “Program of Excellence in Glycosciences”, which will not only support collaborative research, but also will provide hands-on laboratory training in the methods of glycosciences to fellows.

Figure 2
Glycomic complexity reflects cellular complexity

Thus, while our knowledge about the biology of glycans and glycomics continues to lag behind more mainstream fields of genomics and proteomics, technological advances in glycomics in the last five years have begun to accelerate the integration of glycobiology into the other major fields of biomedical research. A complete mechanistic understanding of the etiology of almost any disease will depend upon the elucidation of the functions of all post-translational modifications, but will especially depend upon our understanding the many roles of glycans, the most abundant and structurally diverse type of post-translational modification.

Acknowledgments

We thank Dr. Chad Slawson for helpful suggestions. Original research in the author's laboratory was supported by NIH grants, R01CA42486, R01 DK61671 and R24 DK084949.

Footnotes

Publisher's Disclaimer: This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final citable form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.

References

  • An HJ, Froehlich JW, Lebrilla CB. Determination of glycosylation sites and site-specific heterogeneity in glycoproteins. Curr Opin Chem Biol. 2009;13:421–426. [PMC free article] [PubMed]
  • Aoki-Kinoshita KF. An introduction to bioinformatics for glycomics research. PLoS Comput Biol. 2008;4:e1000075. [PMC free article] [PubMed]
  • Apweiler R, Hermjakob H, Sharon N. On the frequency of protein glycosylation, as deduced from analysis of the SWISS-PROT database. Biochim Biophys Acta. 1999;1473:4–8. [PubMed]
  • Bertozzi CR, Sasisekharan R. Glycomics. In: Varki A, Cummings RD, Esko JD, Freeze HH, Stanley P, Bertozzi CR, Hart GW, Etzler ME, editors. Essentials of Glycobiology. 2nd. Cold Spring Harbor (NY): Cold Spring Harbor Laboratory Press; 2009.
  • Cantarel BL, Coutinho PM, Rancurel C, Bernard T, Lombard V, Henrissat B. The Carbohydrate-Active EnZymes database (CAZy): an expert resource for Glycogenomics. Nucleic Acids Res. 2009;37:D233–238. [PMC free article] [PubMed]
  • Ceroni A, Maass K, Geyer H, Geyer R, Dell A, Haslam SM. GlycoWorkbench: a tool for the computer-assisted annotation of mass spectra of glycans. J Proteome Res. 2008;7:1650–1659. [PubMed]
  • Chang J, Patton JT, Sarkar A, Ernst B, Magnani JL, Frenette PS. GMI-1070, a novel pan-selectin antagonist, reverses acute vascular occlusions in sickle cell mice. Blood. 2010;116:1779–1786. [PMC free article] [PubMed]
  • Cohen M, Varki A. The sialome--far more than the sum of its parts. OMICS. 2010;14:455–464. [PubMed]
  • Cummings RD. The repertoire of glycan determinants in the human glycome. Mol Biosyst. 2009;5:1087–1104. [PubMed]
  • Endo T. Akira Kobata: a man who established the structural basis for glycobiology of N-linked sugar chains. J Biochem. 2010;147:9–17. [PubMed]
  • Goldberg D, Sutton-Smith M, Paulson J, Dell A. Automatic annotation of matrix-assisted laser desorption/ionization N-glycan spectra. Proteomics. 2005;5:865–875. [PubMed]
  • Gupta G, Surolia A, Sampathkumar SG. Lectin microarrays for glycomic analysis. OMICS. 2010;14:419–436. [PubMed]
  • Hart GW, Housley MP, Slawson C. Cycling of O-linked beta-N-acetylglucosamine on nucleocytoplasmic proteins. Nature. 2007;446:1017–1022. [PubMed]
  • Hsu KL, Pilobello KT, Mahal LK. Analyzing the dynamic bacterial glycome with a lectin microarray approach. Nat Chem Biol. 2006;2:153–157. [PubMed]
  • Krishnamoorthy L, Mahal LK. Glycomic analysis: an array of technologies. ACS Chem Biol. 2009;4:715–732. [PMC free article] [PubMed]
  • Lairson LL, Henrissat B, Davies GJ, Withers SG. Glycosyltransferases: structures, functions, and mechanisms. Annu Rev Biochem. 2008;77:521–555. [PubMed]
  • Lajoie P, Goetz JG, Dennis JW, Nabi IR. Lattices, rafts, and scaffolds: domain regulation of receptor signaling at the plasma membrane. J Cell Biol. 2009;185:381–385. [PMC free article] [PubMed]
  • Laremore TN, Leach FE, 3rd, Solakyildirim K, Amster IJ, Linhardt RJ. Glycosaminoglycan characterization by electrospray ionization mass spectrometry including fourier transform mass spectrometry. Methods Enzymol. 2010;478:79–108. [PMC free article] [PubMed]
  • Ly M, Laremore TN, Linhardt RJ. Proteoglycomics: recent progress and future challenges. OMICS. 2010;14:389–399. [PMC free article] [PubMed]
  • Moloney DJ, Panin VM, Johnston SH, Chen J, Shao L, Wilson R, Wang Y, Stanley P, Irvine KD, Haltiwanger RS, et al. Fringe is a glycosyltransferase that modifies Notch. Nature. 2000;406:369–375. [PubMed]
  • North SJ, Jang-Lee J, Harrison R, Canis K, Ismail MN, Trollope A, Antonopoulos A, Pang PC, Grassi P, Al-Chalabi S, et al. Mass spectrometric analysis of mutant mice. Methods Enzymol. 2010;478:27–77. [PubMed]
  • Packer NH, von der Lieth CW, Aoki-Kinoshita KF, Lebrilla CB, Paulson JC, Raman R, Rudd P, Sasisekharan R, Taniguchi N, York WS. Frontiers in glycomics: bioinformatics and biomarkers in disease. An NIH white paper prepared from discussions by the focus groups at a workshop on the NIH campus, Bethesda MD (September 11-13, 2006) Proteomics. 2008;8:8–20. [PubMed]
  • Paulson JC, Blixt O, Collins BE. Sweet spots in functional glycomics. Nat Chem Biol. 2006;2:238–248. [PubMed]
  • Raman R, Venkataraman M, Ramakrishnan S, Lang W, Raguram S, Sasisekharan R. Advancing glycomics: implementation strategies at the consortium for functional glycomics. Glycobiology. 2006;16:82R–90R. [PubMed]
  • Reid GE, Stephenson JL, Jr, McLuckey SA. Tandem mass spectrometry of ribonuclease A and B: N-linked glycosylation site analysis of whole protein ions. Anal Chem. 2002;74:577–583. [PubMed]
  • Rudd PM, Dwek RA. Glycosylation: Heterogeneity and the 3D structure of proteins. CritRevBiochemMolBiol. 1997;32:1–100. [PubMed]
  • Schachter H, Freeze HH. Glycosylation diseases: quo vadis? Biochim Biophys Acta. 2009;1792:925–930. [PMC free article] [PubMed]
  • Schauer R. Sialic acids as regulators of molecular and cellular interactions. Curr Opin Struct Biol. 2009;19:507–514. [PubMed]
  • Smith DF, Song X, Cummings RD. Use of glycan microarrays to explore specificity of glycan-binding proteins. Methods Enzymol. 2010;480:417–444. [PubMed]
  • Spiro RG. Protein glycosylation: nature, distribution, enzymatic formation, and disease implications of glycopeptide bonds. Glycobiology. 2002;12:43R–56R. [PubMed]
  • Swiedler SJ, Freed JH, Tarentino AL, Plummer TH, Jr, Hart GW. Oligosaccharide microheterogeneity of the murine major histocompatibility antigens. Reproducible site-specific patterns of sialylation and branching in asparagine-linked oligosaccharides. JBiolChem. 1985;260:4046–4054. [PubMed]
  • Taniguchi N. Human disease glycomics/proteome initiative (HGPI) Mol Cell Proteomics. 2008;7:626–627. [PubMed]
  • Taylor AD, Hancock WS, Hincapie M, Taniguchi N, Hanash SM. Towards an integrated proteomic and glycomic approach to finding cancer biomarkers. Genome Med. 2009;1:57. [PMC free article] [PubMed]
  • Tian Y, Gurley K, Meany DL, Kemp CJ, Zhang H. N-linked glycoproteomic analysis of formalin-fixed and paraffin-embedded tissues. J Proteome Res. 2009;8:1657–1662. [PMC free article] [PubMed]
  • Vanderschaeghe D, Festjens N, Delanghe J, Callewaert N. Glycome profiling using modern glycomics technology: technical aspects and applications. Biol Chem. 2010;391:149–161. [PubMed]
  • Varki A, Cummings RD, Esko JD, Freeze HH, Stanley P, Bertozzi CR, Hart GW, Etzler ME. Essentials of Glycobiology. 2nd. Cold Spring Harbor, NY: Cold Spring Harbor Laboratory Press; 2009.
  • Yoshida-Moriguchi T, Yu L, Stalnaker SH, Davis S, Kunz S, Madson M, Oldstone MB, Schachter H, Wells L, Campbell KP. O-mannosyl phosphorylation of alpha-dystroglycan is required for laminin binding. Science. 2010;327:88–92. [PMC free article] [PubMed]
  • Zaia J. Mass spectrometry and glycomics. OMICS. 2010;14:401–418. [PMC free article] [PubMed]
  • Zeidan Q, Hart GW. The intersections between O-GlcNAcylation and phosphorylation: implications for multiple signaling pathways. J Cell Sci. 2010;123:13–22. [PMC free article] [PubMed]
  • Zielinska DF, Gnad F, Wisniewski JR, Mann M. Precision mapping of an in vivo N-glycoproteome reveals rigid topological and sequence constraints. Cell. 2010;141:897–907. [PubMed]
PubReader format: click here to try

Formats:

Related citations in PubMed

See reviews...See all...

Cited by other articles in PMC

See all...

Links

  • Cited in Books
    Cited in Books
    PubMed Central articles cited in books
  • MedGen
    MedGen
    Related information in MedGen
  • PubMed
    PubMed
    PubMed citations for these articles
  • Substance
    Substance
    PubChem Substance links

Recent Activity

Your browsing activity is empty.

Activity recording is turned off.

Turn recording back on

See more...