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A Systems Biology Approach for the Investigation of the Heparin/Heparan Sulfate Interactome*

  • Alessandro Ori
    Footnotes
    Affiliations
    From the Institute of Integrative Biology and Centre for Glycobiology, University of Liverpool, Liverpool L69 7ZB, United Kingdom
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  • Mark C. Wilkinson
    Footnotes
    Affiliations
    From the Institute of Integrative Biology and Centre for Glycobiology, University of Liverpool, Liverpool L69 7ZB, United Kingdom
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  • David G. Fernig
    Correspondence
    To whom correspondence should be addressed: Inst. of Integrative Biology and Centre for Glycobiology, Biosciences Bldg., University of Liverpool, Crown St., Liverpool L69 7ZB, UK. Tel.: 44-151-795-4471; Fax: 44-151-795-4406;
    Footnotes
    Affiliations
    From the Institute of Integrative Biology and Centre for Glycobiology, University of Liverpool, Liverpool L69 7ZB, United Kingdom
    Search for articles by this author
  • Author Footnotes
    * This work was supported by the European Commission Marie Curie Early Stage Training Program MolFun (to A. O.), the Cancer and Polio Research Fund Laboratories, and the North West Cancer Research Fund (to D. G. F.).
    The on-line version of this article (available at http://www.jbc.org) contains supplemental Methods, Results, Figs. 1–5, and Tables 1–7.
    1 Present address: Structural and Computational Biology Unit, European Molecular Biology Laboratory, 69117 Heidelberg, Germany.
    2 Both authors made equal contributions to this work.
Open AccessPublished:March 30, 2011DOI:https://doi.org/10.1074/jbc.M111.228114
      A large body of evidence supports the involvement of heparan sulfate (HS) proteoglycans in physiological processes such as development and diseases including cancer and neurodegenerative disorders. The role of HS emerges from its ability to interact and regulate the activity of a vast number of extracellular proteins including growth factors and extracellular matrix components. A global view on how protein-HS interactions influence the extracellular proteome and, consequently, cell function is currently lacking. Here, we systematically investigate the functional and structural properties that characterize HS-interacting proteins and the network they form. We collected 435 human proteins interacting with HS or the structurally related heparin by integrating literature-derived and affinity proteomics data. We used this data set to identify the topological features that distinguish the heparin/HS-interacting network from the rest of the extracellular proteome and to analyze the enrichment of gene ontology terms, pathways, and domain families in heparin/HS-binding proteins. Our analysis revealed that heparin/HS-binding proteins form a highly interconnected network, which is functionally linked to physiological and pathological processes that are characteristic of higher organisms. Therefore, we then investigated the existence of a correlation between the expansion of domain families characteristic of the heparin/HS interactome and the increase in biological complexity in the metazoan lineage. A strong positive correlation between the expansion of the heparin/HS interactome and biosynthetic machinery and organism complexity emerged. The evolutionary role of HS was reinforced by the presence of a rudimentary HS biosynthetic machinery in a unicellular organism at the root of the metazoan lineage.

      Introduction

      A major challenge for the postgenomics era is to establish functional and structural relationships between the components of biological systems. In the last decade, the development of high throughput methods for the study of genetic interactions (
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      • Hogue C.W.
      • Bussey H.
      • Andrews B.
      • Tyers M.
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      ) and protein-protein interactions (
      • Uetz P.
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      • Cagney G.
      • Mansfield T.A.
      • Judson R.S.
      • Knight J.R.
      • Lockshon D.
      • Narayan V.
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      • Conover D.
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      • Yang M.
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      ,
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      • Krause R.
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      • Marzioch M.
      • Bauer A.
      • Schultz J.
      • Rick J.M.
      • Michon A.M.
      • Cruciat C.M.
      • Remor M.
      • Höfert C.
      • Schelder M.
      • Brajenovic M.
      • Ruffner H.
      • Merino A.
      • Klein K.
      • Hudak M.
      • Dickson D.
      • Rudi T.
      • Gnau V.
      • Bauch A.
      • Bastuck S.
      • Huhse B.
      • Leutwein C.
      • Heurtier M.A.
      • Copley R.R.
      • Edelmann A.
      • Querfurth E.
      • Rybin V.
      • Drewes G.
      • Raida M.
      • Bouwmeester T.
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      • Seraphin B.
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      • Neubauer G.
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      ,
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      • Cagney G.
      • Yu H.
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      • Guo X.
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      • Shales M.
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      • Robinson M.D.
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      • Canadien V.
      • Lalev A.
      • Mena F.
      • Wong P.
      • Starostine A.
      • Canete M.M.
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      • Wu S.
      • Orsi C.
      • Collins S.R.
      • Chandran S.
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      • Rilstone J.J.
      • Gandi K.
      • Thompson N.J.
      • Musso G.
      • St Onge P.
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      • Butland G.
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      • Shilatifard A.
      • O'Shea E.
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      • Hughes T.R.
      • Parkinson J.
      • Gerstein M.
      • Wodak S.J.
      • Emili A.
      • Greenblatt J.F.
      ) has enabled the collection of large data sets describing binary relationships between primary gene products. The accumulation of these large data sets required innovative ways to represent and analyze molecular networks, thus stimulating the development of a new discipline known as network biology (
      • Jeong H.
      • Mason S.P.
      • Barabási A.L.
      • Oltvai Z.N.
      ,
      • Barabási A.L.
      • Oltvai Z.N.
      ,
      • Grove C.A.
      • De Masi F.
      • Barrasa M.I.
      • Newburger D.E.
      • Alkema M.J.
      • Bulyk M.L.
      • Walhout A.J.
      ,
      • Taylor I.W.
      • Linding R.
      • Warde-Farley D.
      • Liu Y.
      • Pesquita C.
      • Faria D.
      • Bull S.
      • Pawson T.
      • Morris Q.
      • Wrana J.L.
      ). This new approach has been successfully used to integrate data from different experimental platforms (
      • Ideker T.
      • Thorsson V.
      • Ranish J.A.
      • Christmas R.
      • Buhler J.
      • Eng J.K.
      • Bumgarner R.
      • Goodlett D.R.
      • Aebersold R.
      • Hood L.
      ), infer properties of interaction networks by applying statistical theories (
      • Barabási A.L.
      • Oltvai Z.N.
      ), assign protein function (
      • Bandyopadhyay S.
      • Sharan R.
      • Ideker T.
      ), identify network signatures characteristic of diseases such as cancer (
      • Taylor I.W.
      • Linding R.
      • Warde-Farley D.
      • Liu Y.
      • Pesquita C.
      • Faria D.
      • Bull S.
      • Pawson T.
      • Morris Q.
      • Wrana J.L.
      ,
      • Bandyopadhyay S.
      • Sharan R.
      • Ideker T.
      ), and investigate the evolution of interaction networks (
      • Fraser H.B.
      ,
      • Beltrao P.
      • Serrano L.
      ). However, the chemical complexity of secondary gene products such as glycans and lipids and the technical challenges associated with the study of their interactions have generated a gap in our current models of interaction networks, and as a consequence, the interactions of proteins with secondary gene products such as glycosaminoglycans (GAGs)
      The abbreviations used are: GAG, glycosaminoglycan; B3GA3, galactosylgalactosylxylosylprotein 3-β-glucuronosyltransferase 3; B3GT6, β-1,3-galactosyltransferase 6; B4GT7, xylosylprotein 4-β-galactosyltransferase 7; ECM, extracellular matrix; EXT, exostosin/heparan sulfate polymerase; EXTL3, exostosin-like 3/glucosamine transferase; GlcUA, glucuronic acid; GlcNAc, N-acetylglucosamine; GLCE, glucuronic acid C5-epimerase; GO, gene ontology; HBP, heparin-binding protein; HBS, heparin-binding site; HS, heparan sulfate; HS2ST, heparan sulfate 2-O-sulfotranferase; HS3ST, heparan sulfate 3-O-sulfotranferase; HS6ST, heparan sulfate 6-O-sulfotranferase; HSPG, heparan sulfate proteoglycan; KEGG, Kyoto encyclopedia of genes and genomes; NDST, heparan sulfate N-deacetylase/N-sulfotransferase; PCC, Pearson correlation coefficient; SCOP, structural classification of proteins; taxid, NCBI taxonomy identifier.
      have been excluded from the above systematic analyses.
      The GAGs are linear polysaccharides whose synthesis is not template-driven. As the most complex of biological polymers, they provide access to a vast chemical information space. This has been exploited in eumetazoans to provide structural frameworks and active mediation of cell-cell communication, both absolute requirements for multicellularity. The sulfated GAGs such as heparin/heparan sulfate (HS) are synthesized and serine-linked to the core proteins of proteoglycans (HSPGs) and are located on the plasma membrane and in the extracellular matrix (ECM). The chemical complexity of heparin/HS arises from the initially synthesized monotonous polymer being extensively modified (epimerization and sulfation at various positions in the sugar rings). These modifications are substoichiometric and grouped to produce characteristic domains, which vary in size and number within each chain (
      • Turnbull J.E.
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      ,
      • Murphy K.J.
      • Merry C.L.
      • Lyon M.
      • Thompson J.E.
      • Roberts I.S.
      • Gallagher J.T.
      ). Analysis of functional structures in vivo demonstrates that there is specific regulation of the structures of heparin/HS that are expressed at the cellular level (
      • Allen B.L.
      • Rapraeger A.C.
      ,
      • Bornemann D.J.
      • Park S.
      • Phin S.
      • Warrior R.
      ,
      • Ori A.
      • Wilkinson M.C.
      • Fernig D.G.
      ,
      • Thompson S.M.
      • Jesudason E.C.
      • Turnbull J.E.
      • Fernig D.G.
      ), and thus, it seems that biology exploits a substantial amount of the chemical information space of heparin/HS. The functions of heparin/HS are exerted through their capacity to engage protein ligands. The consequences of these interactions range from elaborating large scale structures to regulating the gradient formation and signaling activities of growth factors, cytokines, and morphogens and the localization and activity of extracellular enzymes (Refs.
      • Bornemann D.J.
      • Park S.
      • Phin S.
      • Warrior R.
      ,
      • Vyas N.
      • Goswami D.
      • Manonmani A.
      • Sharma P.
      • Ranganath H.A.
      • VijayRaghavan K.
      • Shashidhara L.S.
      • Sowdhamini R.
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      , and
      • Yu S.R.
      • Burkhardt M.
      • Nowak M.
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      • Brand M.
      ; for a review, see Ref.
      • Ori A.
      • Wilkinson M.C.
      • Fernig D.G.
      ). The scope of these functions is evidenced by the size of the human heparin/HS interactome: 216 proteins in a review published in 2008 (
      • Ori A.
      • Wilkinson M.C.
      • Fernig D.G.
      ). Many pathogens express proteins that interact with heparin/HS as part of their molecular adaptation to infection of mammals (
      • Chen Y.
      • Götte M.
      • Liu J.
      • Park P.W.
      ). Thus, HSPGs are key players in molecular networks driving biological phenomena such as development (
      • Lin X.
      ), inflammation and immune response (
      • Parish C.R.
      ,
      • Handel T.M.
      • Johnson Z.
      • Crown S.E.
      • Lau E.K.
      • Proudfoot A.E.
      ), and disease (
      • Chen Y.
      • Götte M.
      • Liu J.
      • Park P.W.
      ,
      • Fuster M.M.
      • Esko J.D.
      ).
      The first aim of this study was to integrate and rationalize available data on heparin/HS-protein interactions. The current coverage of heparin/HS-protein interactions in public databases is largely incomplete (Table 1). Therefore, a literature mining effort (
      • Ori A.
      • Wilkinson M.C.
      • Fernig D.G.
      ) was combined with an affinity proteomics approach for the identification of heparin/HS-binding proteins (HBPs) (supplemental Results and supplemental Figs. 1 and 2), and data were retrieved from public databases to generate a comprehensive list of the interactions between heparin/HS and proteins described so far. The term “HBP” is used because heparin is commonly used as an experimental proxy for the sulfated domains of HS, and many interactions have not been validated with HS. This data set then enabled a new systematic way of analyzing heparin/HS-protein interactions using tools widely applied in genomics and proteomics studies. The system-level analysis allowed the investigation of how HBPs interact with each other by computing the topological properties of the network they form and the identification of functional and structural features that are associated with the heparin/HS binding activity. Finally, to generate insights into the role of HSPGs in the evolution of multicellular organisms, the presence of orthologs of HS biosynthetic enzymes in the genome of the choanoflagellate Monosiga brevicollis was investigated. Choanoflagellates are unicellular and colony-forming organisms found in marine and freshwater environments. They use a single apical flagellum surrounded by a collar of actin-filled microvilli to swim and capture bacterial prey (
      • Abedin M.
      • King N.
      ). Because choanoflagellates are not metazoans and did not evolve from sponges or more recently derived metazoan phyla, they are indicated as the last unicellular organisms that evolved before the origin and diversification of metazoans (
      • King N.
      • Westbrook M.J.
      • Young S.L.
      • Kuo A.
      • Abedin M.
      • Chapman J.
      • Fairclough S.
      • Hellsten U.
      • Isogai Y.
      • Letunic I.
      • Marr M.
      • Pincus D.
      • Putnam N.
      • Rokas A.
      • Wright K.J.
      • Zuzow R.
      • Dirks W.
      • Good M.
      • Goodstein D.
      • Lemons D.
      • Li W.
      • Lyons J.B.
      • Morris A.
      • Nichols S.
      • Richter D.J.
      • Salamov A.
      • Sequencing J.G.
      • Bork P.
      • Lim W.A.
      • Manning G.
      • Miller W.T.
      • McGinnis W.
      • Shapiro H.
      • Tjian R.
      • Grigoriev I.V.
      • Rokhsar D.
      ). Previous works indicate the presence in the genome of M. brevicollis of protein families that were thought to be exclusive to multicellular organisms (
      • Abedin M.
      • King N.
      ,
      • King N.
      • Westbrook M.J.
      • Young S.L.
      • Kuo A.
      • Abedin M.
      • Chapman J.
      • Fairclough S.
      • Hellsten U.
      • Isogai Y.
      • Letunic I.
      • Marr M.
      • Pincus D.
      • Putnam N.
      • Rokas A.
      • Wright K.J.
      • Zuzow R.
      • Dirks W.
      • Good M.
      • Goodstein D.
      • Lemons D.
      • Li W.
      • Lyons J.B.
      • Morris A.
      • Nichols S.
      • Richter D.J.
      • Salamov A.
      • Sequencing J.G.
      • Bork P.
      • Lim W.A.
      • Manning G.
      • Miller W.T.
      • McGinnis W.
      • Shapiro H.
      • Tjian R.
      • Grigoriev I.V.
      • Rokhsar D.
      ,
      • King N.
      • Hittinger C.T.
      • Carroll S.B.
      ). The presence of functional signaling cascades based on tyrosine phosphorylation has been also demonstrated (
      • King N.
      • Hittinger C.T.
      • Carroll S.B.
      ). For these reasons, the study of M. brevicollis is considered to be crucial for the identification of the molecular networks that were present in the last common ancestor of choanoflagellates and metazoans and that likely contributed to the emergence of multicellularity and the development of animals.
      TABLE 1Current coverage of human HBPs in publicly available databases
      SourceSearch criteriaOutputRef.
      GO consortium (April 2010)GO:0008201 heparin binding109 human genes
      • Ashburner M.
      • Ball C.A.
      • Blake J.A.
      • Botstein D.
      • Butler H.
      • Cherry J.M.
      • Davis A.P.
      • Dolinski K.
      • Dwight S.S.
      • Eppig J.T.
      • Harris M.A.
      • Hill D.P.
      • Issel-Tarver L.
      • Kasarskis A.
      • Lewis S.
      • Matese J.C.
      • Richardson J.E.
      • Ringwald M.
      • Rubin G.M.
      • Sherlock G.
      GO consortium (April 2010)GO:0043395 heparan sulfate binding4 human genes
      • Ashburner M.
      • Ball C.A.
      • Blake J.A.
      • Botstein D.
      • Butler H.
      • Cherry J.M.
      • Davis A.P.
      • Dolinski K.
      • Dwight S.S.
      • Eppig J.T.
      • Harris M.A.
      • Hill D.P.
      • Issel-Tarver L.
      • Kasarskis A.
      • Lewis S.
      • Matese J.C.
      • Richardson J.E.
      • Ringwald M.
      • Rubin G.M.
      • Sherlock G.
      MatrixDB (April 2010)Heparin + heparan sulfate90 human entries
      • Chautard E.
      • Ballut L.
      • Thierry-Mieg N.
      • Ricard-Blum S.
      UniProtKB (Release 2010_04)KW-0358 heparin binding66 human genes
      • UniProt Consortium
      Literature-based review216 human genes
      • Ori A.
      • Wilkinson M.C.
      • Fernig D.G.

      DISCUSSION

      The analysis undertaken of the heparin/HS interactome allowed the investigation of the properties of the heparin/HS-interacting network of protein-protein interaction and the analysis at a system level of the functional and structural features characterizing HBPs. The heparin/HS interactome was built combining literature mining, data retrieval from public databases, and proteomics experimental data. The affinity proteomics strategy described in the supplementary information led to the identification of 147 extracellular proteins of which 32 were previously described HBPs (supplemental Table 1). The remaining 115 newly discovered HBPs were also included for the analysis of the heparin/HS interactome, although these interactions will require independent experimental validation. The resulting data set included 435 human proteins of which most are extracellular (supplemental Table 5). The analysis of the heparin/HS-interacting network revealed that HBPs tend to form more highly clustered modules than other extracellular proteins. These clusters can assemble both at the cell surface and in the ECM, and they often also represent functional modules. From a functional point of view, the heparin/HS interactome is strongly associated with biological processes characteristic of multicellular organisms and with pathways that are crucial for the conversion of extracellular cues into intracellular signaling events and finally into a phenotypic response. These processes and pathways are central to complex biological phenomena particular to higher organisms such as development and the immune response, and they are consequently linked to pathological conditions such as cancer and neurodegenerative disorders. In this perspective, potential intracellular roles of HSPGs could provide additional mechanisms for GAG-mediated regulation of intracellular signaling (
      • Chen L.
      • Sanderson R.D.
      ). The structural analysis of the heparin/HS interactome revealed the existence of two main categories of domains associated with heparin/HS binding activity: domains that are characteristic of soluble single domain proteins and domains that occur mainly in multidomain proteins and that have been assembled during evolution in different architectures. From an evolutionary perspective, the expansion of domains associated with the heparin/HS interactome strongly correlates with an increase in organism complexity that is independent of their nature. A similar correlation was already described for domains and proteins generically associated with extracellular processes (
      • Vogel C.
      • Chothia C.
      ,
      • Huxley-Jones J.
      • Pinney J.W.
      • Archer J.
      • Robertson D.L.
      • Boot-Handford R.P.
      ); however, also within this set, the heparin/HS interactome-associated domains display a statistically significant higher correlation than other extracellular domains. It has been shown that the evolutionary rate of the extracellular proteome is faster then the intracellular proteome probably due to the less chemically constrained environment faced by extracellular proteins (
      • Julenius K.
      • Pedersen A.G.
      ). This evolutionary plasticity of the extracellular proteome could have been a driving force for the organization of more complex systems of intercellular communication and organization. The functional and structural link between the heparin/HS interactome and biological processes characteristic of complex organisms and the fact that HBPs are more correlated than other extracellular proteins with an increase in organism complexity strongly suggest a pivotal role of HSPGs in driving the evolution of multicellular and higher organisms. In fact, the expansion of enzymes and core proteins responsible for the synthesis and localization of HS chains also correlates with an increase in organism complexity in the metazoan lineage. The core HSPG biosynthetic machinery was thought to have evolved in early eumetazoans concomitantly with the emergence of multicellularity (
      • Freilich S.
      • Goldovsky L.
      • Ouzounis C.A.
      • Thornton J.M.
      ). Biochemical data describing the presence of heparin/HS-like GAGs in phyla at the root of the eumetazoan lineage such as Cnidaria and Ctenophora (
      • Medeiros G.F.
      • Mendes A.
      • Castro R.A.
      • Baú E.C.
      • Nader H.B.
      • Dietrich C.P.
      ,
      • Yamada S.
      • Morimoto H.
      • Fujisawa T.
      • Sugahara K.
      ) supported this view. However, the presence of orthologs of key HS biosynthetic enzymes in the choanoflagellate M. brevicollis suggests that GAGs are likely to be a molecular innovation that predates the origin of metazoans. HSPGs might have been a critical step for the assembly of an extracellular network of proteins required for the structural organization of the extracellular space and for the establishment of cell-cell communication and cell differentiation. Later on, gene duplication events, in particular the whole genome duplications that occurred at the root of the vertebrate lineage (
      • Panopoulou G.
      • Poustka A.J.
      ), contributed to expand the repertoire of both HSPG biosynthetic enzymes and their interacting partners on which evolution could act. The fact that domains characteristic of the heparin/HS interactome are strongly correlated with organism complexity could indicate that their expansion has been one of the driving forces toward the organization of the more sophisticated and tunable extracellular networks that are required for the development of higher organisms and for the control of organism-level biological processes such as the establishment of an immune system. In support of this, others have already proposed HSPGs as key molecules for the emergence of neural connectivity (
      • Van Vactor D.
      • Wall D.P.
      • Johnson K.G.
      ,
      • Lee J.S.
      • Chien C.B.
      ). The authors collected a series of experimental evidences obtained in different model organisms describing the specific involvement of HSPGs in all the key processes required for the establishment of neural connectivity including axon guidance, neuron-target interaction, and synapse development (
      • Van Vactor D.
      • Wall D.P.
      • Johnson K.G.
      ). Similar to what has been proposed here, the authors suggested a role for HSPGs as versatile extracellular scaffolds that modulate extracellular cues influencing the response of neurons to their environment (
      • Van Vactor D.
      • Wall D.P.
      • Johnson K.G.
      ). In the future, heparin affinity proteomics strategies similar to that described in the supplemental information could be implemented in combination with quantitative mass spectrometry techniques such as targeted proteomics (
      • Domon B.
      • Aebersold R.
      ) and staple isotope labeling with amino acids in cell culture (
      • Ong S.E.
      • Blagoev B.
      • Kratchmarova I.
      • Kristensen D.B.
      • Steen H.
      • Pandey A.
      • Mann M.
      ) to investigate dynamic changes of the heparin/HS interactome associated, for example, with different developmental stages or pathological conditions. Such data, complemented by the characterization of the dynamic changes in HS structure, could be extremely valuable to elucidate HSPG-mediated mechanisms involved in the control of physiological and pathological processes. This opens the door to the design of new, network-based therapeutic strategies targeting multiple protein-glycan interactions that are associated with multifactorial diseases. Finally, the structural and functional characterization of the proteome and glycome of organisms at the root of the metazoan lineage could illuminate the role of protein and glycan co-evolution in the assembly of the extracellular molecular networks necessary for the development of complex forms of life.

      Acknowledgments

      We thank Dr. Martin Beck and the European Molecular Biology Laboratory Proteomic Core Facility for help with mass spectrometry data acquisition and analysis, Dr. Olga Vasieva and Dr. Krzysztof Wicher for many helpful discussions and bioinformatics support, and Hassanul Choudhury for technical assistance.

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