Proteins encountered in biological and environmental systems bind to engineered nanomaterials (ENMs) to form a protein corona (PC) that alters the surface chemistry, reactivity, and fate of the ENMs. Complexities such as the diversity of the PC and variation with ENM properties and reaction conditions make the PC population difficult to predict. Here, we support the development of predictive models for PC populations by relating biophysicochemical characteristics of proteins, ENMs, and solution conditions to PC formation using random forest classification. The resulting model offers a predictive analysis into the population of PC proteins in Ag ENM systems of various ENM size and surface coatings. With an area under the receiver operating characteristic curve of 0.83 and F1-score of 0.81, a model with strong performance has been constructed based upon experimental data. The weighted contribution of each variable provides recommendations for mechanistic models based upon protein enrichment classification results. Protein biophysical properties such as pI and weight are weighted heavily. Yet, ENM size, surface charge, and solution ionic strength also proved essential to an accurate model. The model can be readily modified and applied to other ENM PC populations. The model presented here represents the first step toward robust predictions of PC fingerprints.

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A series of laboratory experiments were developed to introduce first-year chemistry students to nanoscience through a green chemistry approach. Students made and characterized the stability of silver nanoparticles using two different methods: UV-visible spectroscopy and dynamic light scattering. They then assessed the ecotoxicity of silver nanoparticles in Escherichia coli sublethal growth curve assays. Bacterial growth was monitored via optical density and carbon dioxide measurements. Finally, students designed and implemented their own nanomaterial characterization and ecotoxicity experiments based upon the insights gained in previous tests. The experiments translated current research in sustainable nanomaterials to an undergraduate population while introducing them to research methodology and experiences early in their undergraduate career. Moreover, the experiments emphasized the interdisciplinary nature of the sciences to provide real-world applications and connect concepts learned within general chemistry lecture and lab to other classes commonly taken by first-year STEM students, including biology, materials science, and environmental sciences.

BackgroundIn a biological system, an engineered nanomaterial (ENM) surface is altered by adsorbed proteins that modify ENM fate and toxicity. Thus far, protein corona characterizations have focused on protein adsorption, interaction strength, and downstream impacts on cell interactions. Given previous reports of Ag ENM disruption of Cu trafficking, this study focuses on Ag ENM interactions with a model Cu metalloprotein, Cu(II) azurin. The study provides evidence of otherwise overlooked ENM-protein chemical reactivity within the corona: redox activity.ResultsCitrate-coated Ag ENMs of various sizes (10–40 nm) reacted with Cu(II) azurin resulted in an order of magnitude more dissolved ionic silver (Ag(I)(aq)) than samples of Ag ENMs only, ENMs mixed Cu(II) ions, or control proteins such as cytochrome c and horse radish peroxidase. This dramatic increase in ENM oxidative dissolution was observed even when Cu(II) azurin was combined with a diverse mixture of Escherchia coli proteins to mimic the complexity of the cellular conona. SDS PAGE results confirm that the multiprotein ENM corona includes azurin. A Cu(I)(aq) colorimetric indicator confirms Cu(II) azurin reduction upon interaction with Ag ENMs, but not with the addition of ionic silver, Ag(I)(aq).ConclusionsCu(II) azurin and 10–40 nm Ag ENMs react to catalyze Ag ENM oxidative dissolution and reduction of the model Cu metalloprotein. Results push the current evaluation of protein-ENM characterization beyond passive binding interactions and enable the proposal of a mechanism for reactivity between a model Cu metalloprotein and Ag ENMs.Electronic supplementary materialThe online version of this article (doi:10.1186/s12951-016-0160-6) contains supplementary material, which is available to authorized users.