Exposure to nanoparticles can be beneficial, such as the use of nanomedicines, or detrimental, such as the inhalation of metal oxide nanoparticles used in industrial applications. In both cases, there is a pressing need for a quantitative understanding of how nanoparticles interact with biological systems. This research will generate a library of protein-nanoparticle interactions using a carefully controlled set of nanoparticles. Experiments will focus on the interaction of nanoparticles with the proteins found in the blood stream. Use of a robot to automate experiments will increase throughput and reproducibility. The research team will use this library, which will be publicly available, to determine which proteins adsorb on the surface of nanoparticles as a function of nanoparticle diameter and surface properties and then use this library for subsequent cell-nanoparticle experiments. A major limit to generating a protein-nanoparticle library has been the cost associated with protein analysis. The research team will benchmark the use of a faster, less expensive, protein separation method to reduce costs. The use of controlled nanoparticle parameters, in combination with automated sample preparation and low-cost protein analysis, will enable the first quantitative understanding of protein-nanoparticle interactions, important for environmental and industrial nanoparticle exposure, as well as therapeutic and diagnostic applications. This research also provides an ideal training platform for students to address fundamental questions of nanoscience with advances in research automation, training that will be relevant to future academic or industry jobs.
Nanoparticles used in any biological system proteins are exposed to proteins that adsorb on the surface of the nanoparticle forming a protein corona. Modification with neutral polymers can reduce this protein corona, but complete inhibition remains a challenge. Currently lacking is an ability to predict which proteins will adsorb on the surface of a specific nanoparticle. Previous work in this area has been limited by the cost of proteomics, only identifying protein-nanoparticles interactions for small sets of nanoparticles, or have carried out large-scale proteomics on a diverse array of ligands that preclude the identification of trends. This research will generate a protein corona library and then use this library to select nanoparticles for protein- and cellular-level mechanistic studies. To generate sufficient nanoparticles with controlled variation of surface parameters, the research team will automate nanoparticle functionalization using a liquid handling robot. To reduce the costs associated with generating a protein corona library, the team will reduce the time required for peptide separation using capillary electrophoresis instead of liquid chromatography. The corona library will be used to select nanoparticles for mechanistic studies to understand why complement C3 and serum albumin are enriched and under-represented, respectively, in protein coronas, and the effect of these proteins on the subsequent interaction with macrophage cells. The outcomes of this research include the protein corona library, which will be publicly available, automation of nanoparticle functionalization and sample preparation, and a detailed comparison of capillary electrophoresis and liquid chromatography separation for proteomics.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
