Delivery and toxicity are critical issues facing nanomedicine research. Currently, there is limited understanding and connection between the physicochemical properties of a nanomaterial and its interactions with a physiological system. As a result, it remains unclear how to optimally synthesize and chemically modify nanomaterials for in vivo applications. It has been suggested that the physicochemical properties of a nanomaterial after synthesis, known as its "synthetic identity", are not what a cell encounters in vivo. Adsorption of blood components and interactions with phagocytes can modify the size, aggregation state, and interfacial composition of a nanomaterial, giving it a distinct "biological identity". Here, we investigate the role of size and surface chemistry in mediating serum protein adsorption to gold nanoparticles and their subsequent uptake by macrophages. Using label-free liquid chromatography tandem mass spectrometry, we find that over 70 different serum proteins are heterogeneously adsorbed to the surface of gold nanoparticles. The relative density of each of these adsorbed proteins depends on nanoparticle size and poly(ethylene glycol) grafting density. Variations in serum protein adsorption correlate with differences in the mechanism and efficiency of nanoparticle uptake by a macrophage cell line. Macrophages contribute to the poor efficiency of nanomaterial delivery into diseased tissues, redistribution of nanomaterials within the body, and potential toxicity. This study establishes principles for the rational design of clinically useful nanomaterials.

Nanomaterials hold promise as multifunctional diagnostic and therapeutic agents. However, the effective application of nanomaterials is hampered by limited understanding and control over their interactions with complex biological systems. When a nanomaterial enters a physiological environment, it rapidly adsorbs proteins forming what is known as the protein 'corona'. The protein corona alters the size and interfacial composition of a nanomaterial, giving it a biological identity that is distinct from its synthetic identity. The biological identity determines the physiological response including signalling, kinetics, transport, accumulation, and toxicity. The structure and composition of the protein corona depends on the synthetic identity of the nanomaterial (size, shape, and composition), the nature of the physiological environment (blood, interstitial fluid, cell cytoplasm, etc.), and the duration of exposure. In this critical review, we discuss the formation of the protein corona, its structure and composition, and its influence on the physiological response. We also present an 'adsorbome' of 125 plasma proteins that are known to associate with nanomaterials. We further describe how the protein corona is related to the synthetic identity of a nanomaterial, and highlight efforts to control protein-nanomaterial interactions. We conclude by discussing gaps in the understanding of protein-nanomaterial interactions along with strategies to fill them (167 references).

Here we systematically examined the effect of nanoparticle size (10-100 nm) and surface chemistry (i.e., poly(ethylene glycol)) on passive targeting of tumors in vivo. We found that the physical and chemical properties of the nanoparticles influenced their pharmacokinetic behavior, which ultimately determined their tumor accumulation capacity. Interestingly, the permeation of nanoparticles within the tumor is highly dependent on the overall size of the nanoparticle, where larger nanoparticles appear to stay near the vasculature while smaller nanoparticles rapidly diffuse throughout the tumor matrix. Our results provide design parameters for engineering nanoparticles for optimized tumor targeting of contrast agents and therapeutics.

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.