Hongbo Guo

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.

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.

A nanoparticle's physical and chemical properties at the time of cell contact will determine the ensuing cellular response. Aggregation and the formation of a protein corona in the extracellular environment will alter nanoparticle size, shape, and surface properties, giving it a "biological identity" that is distinct from its initial "synthetic identity". The biological identity of a nanoparticle depends on the composition of the surrounding biological environment and determines subsequent cellular interactions. When studying nanoparticle-cell interactions, previous studies have ignored the dynamic composition of the extracellular environment as cells deplete and secrete biomolecules in a process known as "conditioning". Here, we show that cell conditioning induces gold nanoparticle aggregation and changes the protein corona composition in a manner that depends on nanoparticle diameter, surface chemistry, and cell phenotype. The evolution of the biological identity in conditioned media enhances the cell membrane affinity, uptake, and retention of nanoparticles. These results show that dynamic extracellular environments can alter nanoparticle-cell interactions by modulating the biological identity. The effect of the dynamic nature of biological environments on the biological identity of nanoparticles must be considered to fully understand nano-bio interactions and prevent data misinterpretation.

C2H2 zinc finger proteins represent the largest and most enigmatic class of human transcription factors. Their C2H2-ZF arrays are highly variable, indicating that most will have unique DNA binding motifs. However, most of the binding motifs have not been directly determined. In addition, little is known about whether or how these proteins regulate transcription. Most of the ∼700 human C2H2-ZF proteins also contain at least one KRAB, SCAN, BTB, or SET domain, suggesting that they may have common interacting partners and/or effector functions. Here, we report a multifaceted functional analysis of 131 human C2H2-ZF proteins, encompassing DNA binding sites, interacting proteins, and transcriptional response to genetic perturbation. We confirm the expected diversity in DNA binding motifs and genomic binding sites, and provide motif models for 78 previously uncharacterized C2H2-ZF proteins, most of which are unique. Surprisingly, the diversity in protein-protein interactions is nearly as high as diversity in DNA binding motifs: Most C2H2-ZF proteins interact with a unique spectrum of co-activators and co-repressors. Thus, multiparameter diversification likely underlies the evolutionary success of this large class of human proteins.