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CD44 is a major cell surface receptor for the large polydisperse glycosaminoglycan hyaluronan (HA). Binding of the long and flexible HA chains is thought to be stabilized by the multivalent nature of the sugar molecule. In addition, high and low molecular weight forms of HA provoke distinct proinflammatory and anti-inflammatory effects upon binding to CD44 and can deliver either proliferative or antiproliferative signals in appropriate cell types. Despite the importance of such interactions, however, neither the stoichiometry of multivalent HA binding at the cell surface nor the molecular basis for functional distinction between different HA size categories is understood. Here we report on the design of a supported lipid bilayer system that permits quantitative analysis of multivalent binding through presentation of CD44 in a stable, natively oriented manner and at controlled density. Using this system in combination with biophysical techniques, we show that the amount of HA binding to bilayers that are densely coated with CD44 increases as a function of HA size, with half-maximal saturation at ∼30 kDa. Moreover, reversible binding was confined to the smaller HA species (molecular weight of ≤10 kDa), whereas the interaction was essentially irreversible with larger polymers. The amount of bound HA decreased with decreasing receptor surface density, but the stability of binding was not affected. From a physico-chemical perspective, the binding properties of HA share many similarities with the typical behavior of a flexible polymer as it adsorbs onto a homogeneously attractive surface. These findings provide new insight into the multivalent nature of CD44-HA interactions and suggest a molecular basis for the distinct biological properties of different size fractions of hyaluronan.

Original publication

DOI

10.1074/jbc.M110.137562

Type

Journal article

Journal

J Biol Chem

Publication Date

24/09/2010

Volume

285

Pages

30170 - 30180

Keywords

Cell Line, Humans, Hyaluronan Receptors, Hyaluronic Acid, Lipid Bilayers, Models, Chemical, Molecular Weight, Protein Binding