AVS 54th International Symposium
    Biomaterial Interfaces Tuesday Sessions
       Session BI-TuP

Paper BI-TuP14
Protein Adsorption Correlated with Surface Properties of Copolymer Libraries Synthesised as Microarrays

Tuesday, October 16, 2007, 6:00 pm, Room 4C

Session: Biomaterials Interfaces Poster Session
Presenter: M. Taylor, University of Nottingham, UK
Authors: M. Taylor, University of Nottingham, UK
A.J. Urquhart, University of Nottingham, UK
D.G. Anderson, Massachusetts Institute of Technology
R. Langer, Massachusetts Institute of Technology
M.R. Alexander, University of Nottingham, UK
M.C. Davies, University of Nottingham, UK
Correspondent: Click to Email

Combinatorial methods have become increasingly popular as a means of material development, allowing rapid discovery and optimisation of new materials. Micro patterned combinatorial material libraries have been shown to be a useful method of screening materials for a number of biological applications. Protein adsorption to surfaces underpins biological response and is therefore of great importance in both implantation and tissue culture situations. Adsorbed proteins effectively translate the structure of a surface into a biological language that ultimately influences the way cells adhere and function. Hence, understanding why and how different proteins adsorb to different surfaces and the effect this has on cell adhesion and growth is of major importance. In this abstract, we report on the adsorption of fluorescently labelled fibronectin to a spatially patterned micro-arrayed library of 480 novel copolymers designed to illicit a range of surface phenomena. Using partial least squares models, protein adsorption has been related to the data generated from the high-throughput surface analysis of the array, including surface chemistry (ToF-SIMS and XPS) and wettability (contact angle, surface energetics), as well as the data derived from the screening of the adhesion and proliferation of the chicken embryonic stem cells to the copolymer library. Interesting correlations between surface phenomena and biological response have been derived from the large data sets, information that will provide important pointers for controlling cellular interactions with such polymeric surfaces.