Protein corona fingerprinting predicts the cellular interaction of gold and silver nanoparticles
Carl D Walkey1, Jonathan B Olsen, Fayi Song
1Institute of Biomaterials and Biomedical Engineering, ‡Banting and Best Department of Medical Research, §Donnelly Centre for Cellular and Biomolecular Research, ⊥Department of Chemical Engineering, ∥Department of Chemistry, #Department of Materials Science and Engineering, University of Toronto , Toronto, Ontario, Canada M5S 3G9.
Abstract:
Using quantitative models to predict the biological interactions of nanoparticles will accelerate the translation of nanotechnology. Here, we characterized the serum protein corona 'fingerprint' formed around a library of 105 surface-modified gold nanoparticles. Applying a bioinformatics-inspired approach, we developed a multivariate model that uses the protein corona fingerprint to predict cell association 50% more accurately than a model that uses parameters describing nanoparticle size, aggregation state, and surface charge. Our model implicates a set of hyaluronan-binding proteins as mediators of nanoparticle-cell interactions. This study establishes a framework for developing a comprehensive database of protein corona fingerprints and biological responses for multiple nanoparticle types. Such a database can be used to develop quantitative relationships that predict the biological responses to nanoparticles and will aid in uncovering the fundamental mechanisms of nano-bio interactions.
