Abstract
BackgroundAccurate and meaningful dose metrics are a basic requirement for in vitro screening to assess potential health risks of engineered nanomaterials (ENMs). Correctly and consistently quantifying what cells “see,” during an in vitro exposure requires standardized preparation of stable ENM suspensions, accurate characterizatoin of agglomerate sizes and effective densities, and predictive modeling of mass transport. Earlier transport models provided a marked improvement over administered concentration or total mass, but included assumptions that could produce sizable inaccuracies, most notably that all particles at the bottom of the well are adsorbed or taken up by cells, which would drive transport downward, resulting in overestimation of deposition.MethodsHere we present development, validation and results of two robust computational transport models. Both three-dimensional computational fluid dynamics (CFD) and a newly-developed one-dimensional Distorted Grid (DG) model were used to estimate delivered dose metrics for industry-relevant metal oxide ENMs suspended in culture media. Both models allow simultaneous modeling of full size distributions for polydisperse ENM suspensions, and provide deposition metrics as well as concentration metrics over the extent of the well. The DG model also emulates the biokinetics at the particle-cell interface using a Langmuir isotherm, governed by a user-defined dissociation constant, KD, and allows modeling of ENM dissolution over time.ResultsDose metrics predicted by the two models were in remarkably close agreement. The DG model was also validated by quantitative analysis of flash-frozen, cryosectioned columns of ENM suspensions. Results of simulations based on agglomerate size distributions differed substantially from those obtained using mean sizes. The effect of cellular adsorption on delivered dose was negligible for KD values consistent with non-specific binding (> 1 nM), whereas smaller values (≤ 1 nM) typical of specific high-affinity binding resulted in faster and eventual complete deposition of material.ConclusionsThe advanced models presented provide practical and robust tools for obtaining accurate dose metrics and concentration profiles across the well, for high-throughput screening of ENMs. The DG model allows rapid modeling that accommodates polydispersity, dissolution, and adsorption. Result of adsorption studies suggest that a reflective lower boundary condition is appropriate for modeling most in vitro ENM exposures.Electronic supplementary materialThe online version of this article (doi:10.1186/s12989-015-0109-1) contains supplementary material, which is available to authorized users.
Highlights
Accurate and meaningful dose metrics are a basic requirement for in vitro screening to assess potential health risks of engineered nanomaterials (ENMs)
Comparison of Distorted Grid and computational fluid dynamics (CFD) model simulations The Distorted Grid (DG) model is based on a model previously developed for analysis of protein systems via their behavior in an ultracentrifuge [24,25,26,27,28,29,30], which was adapted for particle transport and implemented in MATLAB
In the Computational Fluid Dynamics (CFD) model, particles are initially assigned to compartments of a 3-dimensional grid representation of the suspension column, and a solution of the Navier–Stokes equation is used to calculate the movement of individual particles between compartments
Summary
Accurate and meaningful dose metrics are a basic requirement for in vitro screening to assess potential health risks of engineered nanomaterials (ENMs). Until recently most in vitro studies have reported dose in terms of either an initial administered mass concentration or of a total administered mass [11, 14, 15]. The former assumes that sedimentation either does not occur, or is negligible, and the latter assumes that it is complete, with all of the suspended material instantly transported to the cells at the bottom of the cell culture well. The reality lies between these extremes, and depends upon the intrinsic physicochemical properties of the suspended material, the extrinsic properties of suspending media, and the time course of the exposure
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