Nicholas K. Geitner

Direct observation of a single nanoparticle-ubiquitin corona formation†

The advancement of nanomedicine and the increasing applications of nanoparticles in consumer products have led to administered biological exposure and unintentional environmental accumulation of nanoparticles, causing concerns over the biocompatibility and sustainability of nanotechnology. Upon entering physiological environments, nanoparticles readily assume the form of a nanoparticle-protein corona that dictates their biological identity. Consequently, understanding the structure and dynamics of a nanoparticle-protein corona is essential for predicting the fate, transport, and toxicity of nanomaterials in living systems and for enabling the vast applications of nanomedicine. Here we combined multiscale molecular dynamics simulations and complementary experiments to characterize the silver nanoparticle-ubiquitin corona formation. Notably, ubiquitins competed with citrates for the nanoparticle surface, governed by specific electrostatic interactions. Under a high protein/nanoparticle stoichiometry, ubiquitins formed a multi-layer corona on the particle surface. The binding exhibited an unusual stretched-exponential behavior, suggesting a rich binding kinetics. Furthermore, the binding destabilized the α-helices while increasing the β-sheet content of the proteins. This study revealed the atomic and molecular details of the structural and dynamic characteristics of nanoparticle-protein corona formation.

Competitive Binding of Natural Amphiphiles with Graphene Derivatives

Understanding the transformation of graphene derivatives by natural amphiphiles is essential for elucidating the biological and environmental implications of this emerging class of engineered nanomaterials. Using rapid discrete-molecular-dynamics simulations, we examined the binding of graphene and graphene oxide with peptides, fatty acids, and cellulose, and complemented our simulations by experimental studies of Raman spectroscopy, FTIR, and UV-Vis spectrophotometry. Specifically, we established a connection between the differential binding and the conformational flexibility, molecular geometry, and hydrocarbon content of the amphiphiles. Importantly, our dynamics simulations revealed a Vroman-like competitive binding of the amphiphiles for the graphene oxide substrate. This study provides a mechanistic basis for addressing the transformation, evolution, transport, biocompatibility, and toxicity of graphene derivatives in living systems and the natural environment.

Understanding dendritic polymer–hydrocarbon interactions for oil dispersion

This study examines the interactions of poly(amidoamine) dendrimers and hyperbranched poly(ethyleneimine) polymers with model linear and polyaromatic hydrocarbons. Large-scale complexations were formed for both types of dendritic polymers hosting the linear but not the polyaromatic hydrocarbon. Furthermore, both types of dendritic polymers exhibited a strong and comparable hosting/dispersion capacity for the polyaromatic hydrocarbon, while the hyperbranched polymers at concentrations below 30 μM showed a consistently higher hosting capacity than the dendrimers for the linear hydrocarbon. Such complexity in hosting capacity of the two types of dendritic polymers is attributed to the more hydrophobic interior and less steric hindrance of the hyperbranched polymers for the partitioning of the hydrocarbons.

Structure–Function Relationship of PAMAM Dendrimers as Robust Oil Dispersants

PAMAM dendrimers have recently been investigated as efficient and biocompatible oil dispersants utilizing their encapsulation capacity; however, their high cationic charge density has been shown to be cytotoxic. It is therefore imperative to mitigate cationic charge-induced toxicity and understand the effects of such changes. Presented here is a synergistic experimental and computational approach to examine the effects of varying terminal surface charge on the capacity of dendrimers to disperse model liner, polycyclic aromatic, and hybrid hydrocarbons. Uncharged dendrimers collapse by forming intramolecular hydrogen bonds, which reduce the hosting capability. On the other hand, changing the surface charges from positive to negative greatly shifts the pKa of tertiary amines of the PAMAM dendrimer interior. As a result, the negatively charged dendrimers have a significant percentage of tertiary amines protonated, ∼30%. This unexpected change in the interior protonation state causes electrostatic interactions with the anionic terminal groups, leading to contraction and a marked decrease in hydrocarbon hosting capacity. The present work highlights the robust nature of dendrimer oil dispersion and also illuminates potentially unintended or unanticipated effects of varying dendrimer surface chemistry on their encapsulation or hosting efficacy, which is important for their environmental, industrial, and biomedical applications.

PAMAM Dendrimers and Graphene: Materials for Removing Aromatic Contaminants from Water

We present results from experiments and atomistic molecular dynamics simulations on the remediation of naphthalene by polyamidoamine (PAMAM) dendrimers and graphene oxide (GrO). Specifically, we investigate 3rd-6th generation (G3-G6) PAMAM dendrimers and GrO with different levels of oxidation. The work is motivated by the potential applications of these emerging nanomaterials in removing polycyclic aromatic hydrocarbon contaminants from water. Our experimental results indicate that GrO outperforms dendrimers in removing naphthalene from water. Molecular dynamics simulations suggest that the prominent factors driving naphthalene association to these seemingly disparate materials are similar. Interestingly, we find that cooperative interactions between the naphthalene molecules play a significant role in enhancing their association to the dendrimers and GrO. Our findings highlight that while selection of appropriate materials is important, the interactions between the contaminants themselves can also be important in governing the effectiveness of a given material. The combined use of experiments and molecular dynamics simulations allows us to comment on the possible factors resulting in better performance of GrO in removing polyaromatic contaminants from water.

Binding of cytoskeletal proteins with silver nanoparticles

We have characterized the binding of cytoskeletal proteins, namely, tubulin and actin, with silver nanoparticles using the techniques of dynamic light scattering, UV-Vis spectrophotometry, circular dichroism spectroscopy, hyperspectral imaging, and transmission electron microscopy. Overall, actin displayed a higher propensity than tubulin for silver nanoparticles while both proteins experienced conformational changes upon binding. Conversely, ion release from silver nanoparticles was significantly compromised upon the formation of protein biocoronas, as shown by inductively coupled plasma mass spectroscopy. The implications of cytoskeletal protein biocorona on the transformation and cytotoxicity of silver nanoparticles have been discussed.

Nanoparticle Surface Affinity as a Predictor of Trophic Transfer

Nanoscale materials, whether natural, engineered, or incidental, are increasingly acknowledged as important components in large, environmental systems with potential implications for environmental impact and human health. Mathematical models are a useful tool for handling the rapidly increasing complexity and diversity of these materials and their exposure routes. Presented here is a mathematical model of trophic transfer driven by nanomaterial surface affinity for environmental and biological surfaces, developed in tandem with an experimental functional assay for determining these surface affinities. We found that nanoparticle surface affinity is a strong predictor of uptake through predation in a simple food web consisting of the algae Chlorella vulgaris and daphnid Daphnia magna. The mass of nanoparticles internalized by D. magna through consuming nanomaterial-contaminated algae varied linearly with surface-attachment efficiency. Internalized quantities of gold nanoparticles in D. magna ranged from 8.3 to 23.6 ng/mg for nanoparticle preparations with surface-attachment efficiencies ranging from 0.07 to 1. This model, coupled with the functional-assay approach, may provide a useful screening tool for existing materials as well as a predictive model for their development.

Measuring Nanoparticle Attachment Efficiency in Complex Systems

As process-based environmental fate and transport models for engineered nanoparticles are developed, there is a need for relevant and reliable measures of nanoparticle behavior. The affinity of nanoparticles for various surfaces (α) is one such measure. Measurements of the affinity of nanoparticles obtained by flowing particles through a porous medium are constrained by the types of materials or exposure scenarios that can be configured into such column studies. Utilizing glass beads and kaolinite as model collector surfaces, we evaluate a previously developed mixing method for measuring nanoparticle attachment to environmental surfaces, and validate this method with an equivalent static column system over a range of organic matter concentrations and ionic strengths. We found that, while both impacted heteroaggregation rates in a predictable manner when varied individually, neither dominated when both parameters were varied. The theory behind observed nanoparticle heteroaggregation rates (αβB) to background particles in mixed systems is also experimentally validated, demonstrating both collision frequency (β) and background particle concentration (B) to be independent for use in fate modeling. We further examined the effects of collector particle composition (kaolinite vs glass beads) and nanoparticle surface chemistry (PVP, citrate, or humic acid) on α, and found a strong dependence on both.

Mechanistic Insights from Discrete Molecular Dynamics Simulations of Pesticide–Nanoparticle Interactions

Nanoscale particles have the potential to modulate the transport, lifetimes, and ultimate uptake of pesticides that may otherwise be bound to agricultural soils. Engineered nanoparticles provide a unique platform for studying these interactions. In this study, we utilized discrete molecular dynamics (DMD) as a screening tool for examining nanoparticle-pesticide adsorptive interactions. As a proof-of-concept, we selected a library of 15 pesticides common in the United States and 4 nanomaterials with likely natural or incidental sources, and simulated all possible nanoparticle-pesticide pairs. The resulting adsorption coefficients derived from DMD simulations ranged over several orders of magnitude, and in many cases were significantly stronger than pesticide adsorption on clay surfaces, highlighting the significance of specific nanoscale phases as a preferential media with which pesticides may associate. Binding was found to be significantly enhanced by the capacity to form hydrogen bonds with slightly hydroxylated fullerols, highlighting the importance of considering the precise nature of weathered nanomaterials as opposed to pristine precursors. Results were compared to experimental adsorption studies using selected pesticides, with a Pearson correlation coefficient of 0.97.

Comparative Persistence of Engineered Nanoparticles in a Complex Aquatic Ecosystem

During nanoparticle environmental exposure, presence in the water column is expected to dominate long distance transport as well as initial aquatic organism exposure. Much work has been done to understand potential ecological and toxicological effects of these particles. However, little has been done to date to understand the comparative persistence of engineered particles in realistic environmental systems. Presented here is a study of the water column lifetimes of 3 different classes of nanoparticles prepared with a combination of surface chemistries in wetland mesocosms. We find that, when introduced as a single pulse, all tested nanoparticles persist in the water column for periods ranging from 36 h to 10 days. Specifically, we found a range of nanoparticle residence times in the order Ag > TiO2 > SWCNT > CeO2. We further explored the hypothesis that heteroaggregation was the primary driving factor for nanoparticle removal from the water column in all but one case, and that values of surface affinity (α) measured in the laboratory appear to predict relative removal rates when heteroaggregation dominates. Though persistence in the water column was relatively short in all cases, differences in persistence may play a role in determining nanoparticle fate and impacts and were poorly predicted by currently prevailing benchmarks such as particle surface preparation.