Cross-comparison of protein recognition of sialic acid diversity on two novel sialoglycan microarrays.

Author(s): Padler-Karavani V,  Song X,  Yu H,  Hurtado-Ziola N,  Huang S,  Muthana S,  Chokhawala HA,  Cheng J,  Verhagen A,  Langereis MA,  Kleene R,  Schachner M,  de Groot RJ,  Lasanajak Y,  Matsuda H,  Schwab R,  Chen X,  Smith DF,  Cummings RD,  Varki A

Journal: J Biol Chem

Date: 2012 Jun 29

Major Program(s) or Research Group(s): GLYCO

PubMed ID: 22549775

PMC ID: PMC3391140

Abstract: DNA and protein arrays are commonly accepted as powerful exploratory tools in research. This has mainly been achieved by the establishment of proper guidelines for quality control, allowing cross-comparison between different array platforms. As a natural extension, glycan microarrays were subsequently developed, and recent advances using such arrays have greatly enhanced our understanding of protein-glycan recognition in nature. However, although it is assumed that biologically significant protein-glycan binding is robustly detected by glycan microarrays, there are wide variations in the methods used to produce, present, couple, and detect glycans, and systematic cross-comparisons are lacking. We address these issues by comparing two arrays that together represent the marked diversity of sialic acid modifications, linkages, and underlying glycans in nature, including some identical motifs. We compare and contrast binding interactions with various known and novel plant, vertebrate, and viral sialic acid-recognizing proteins and present a technical advance for assessing specificity using mild periodate oxidation of the sialic acid chain. These data demonstrate both the diversity of sialic acids and the analytical power of glycan arrays, showing that different presentations in different formats provide useful and complementary interpretations of glycan-binding protein specificity. They also highlight important challenges and questions for the future of glycan array technology and suggest that glycan arrays with similar glycan structures cannot be simply assumed to give similar results.