Literature DB >> 10674816

PEG-variant biomaterials as selectively adhesive protein templates: model surfaces for controlled cell adhesion and migration.

E Tziampazis1, J Kohn, P V Moghe.   

Abstract

Our study focused on the role of poly(ethylene glycol) (PEG) in actively regulating the biological responsiveness of protein-adsorbed biomaterials. To this end, we designed PEG-variant biomaterials from a family of tyrosine/PEG-derived polycarbonates to present surfaces ranging from low to intermediate levels of PEG concentration, below the PEG level requisite for complete abolition of protein adsorption. We analyzed the effect of PEG concentration on the amount, conformation and bioactivity of an adsorbed model protein, fibronectin, and on the attachment, adhesion strength and motility of L929 fibroblasts. Our results demonstrate that low levels of PEG can regulate not only the extent but also the conformation and specific bioactivity of adsorbed fibronectin. As the PEG concentration was increased from 0 to 6 mol%, the amount of adsorbed fibronectin decreased linearly yet the fibronectin conformation was altered such that the overall bioactivity of adsorbed fibronectin was uncompromised. We report that the degree of cell attachment varied with PEG concentration in a manner similar to the dependence of fibronectin bioactivity on PEG. In contrast, the nature of cell adhesion strength dependence on PEG paralleled the pattern observed for fibronectin surface concentration. Our studies also indicated that the rate of cell migration was inversely correlated with PEG concentration over a narrow range of PEG concentration. Overall, these results highlight the striking ability of PEG-variant biomaterials to systematically regulate the behavior of adsorbed cell adhesion proteins and, consequently, effect cell functions.

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Year:  2000        PMID: 10674816     DOI: 10.1016/s0142-9612(99)00212-4

Source DB:  PubMed          Journal:  Biomaterials        ISSN: 0142-9612            Impact factor:   12.479


  30 in total

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9.  Cytoskeleton-based forecasting of stem cell lineage fates.

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