Deducing in vivo toxicity of combustion-derived nanoparticles from a cell-free oxidative potency assay and metabolic activation of organic compounds

Abstract

Background: The inhalation of combustion-derived nanoparticles (CDNPs) is believed to cause an oxidative stress response, which in turn may lead to pulmonary or even systemic inflammation.

Objective and methods: In this study we assessed whether the in vivo inflammatory response--which is generally referred to as particle toxicity-of mice to CDNPs can be predicted in vitro by a cell-free ascorbate test for the surface reactivity or, more precisely, oxidative potency (OxPot) of particles.

Results: For six types of CDNPs with widely varying particle diameter (10-50 nm), organic content (OC; 1-20%), and specific Brunauer, Emmett, and Teller (BET) surface area (43-800 m2/g), OxPot correlated strongly with the in vivo inflammatory response (pulmonary polymorphonuclear neutrophil influx 24 hr after intratracheal particle instillation). However, for CDNPs with high organic content, OxPot could not explain the observed inflammatory response, possibly due to shielding of the OxPot of the carbon core of CDNPs by an organic coating. On the other hand, a pathway-specific gene expression screen indicated that, for particles rich in polycyclic aromatic hydrocarbon (PAHs), cytochrome P450 1A1 (CYP1A1) enzyme-mediated biotransformation of bio-available organics may generate oxidative stress and thus enhance the in vivo inflammatory response.

Conclusion: The compensatory nature of both effects (shielding of carbon core and biotransformation of PAHs) results in a good correlation between inflammatory response and BET surface area for all CDNPs. Hence, the in vivo inflammatory response can either be predicted by BET surface area or by a simple quantitative model, based on in vitro OxPot and Cyp1a1 induction.

Keywords: BET; Cyp1a1; air pollution; biotransformation; carbonaceous particles; dose response; nanoparticles; nanotoxicity; organic compounds; oxidative stress; particle toxicity; soot particles; specific surface area; surface toxicity; ultrafine particles.

Figure 1

Cell-free oxidative effect (mean ± SE) of the six types of CDNP displayed as the amount of ascorbate consumed by the respective particle mass (5, 1, and 0.2 μg). *Values that were negatively biased because of their proximity to the saturation level (2.5 nmol) were discarded for the calculation of Ox_Pot (Table 1).

Figure 2

Relationships between the in vitro Ox_Pot, in vivo I_Ef, and BET surface area of the six types of CDNPs. (A ) BET surface area versus I_Ef with the linear regression line. (B) Ox_Pot versus I_Ef (the linear regression line was forced through the origin). (C) BET surface area versus oxidative potency (the linear regression was based on all data points except SootH and DEP).

Figure 3

Protein expression and quantification of selected markers. (A) Protein expression analyzed by immunoblotting. (B) For quantification, signal densities were normalized to ACTB loading control and are displayed relative to the respective expressions in sham controls. CYP1A1 was the only marker that was induced for the known high-OC particles SootH (21-fold) and DEP (1.6-fold). It even was mildly induced for PtxG (1.4-fold).

Figure 4

Immunohistologic staining of CYP1A1 protein expression in lungs 24 hr after 20 μg particle instillation showed broad positive staining in epithelial cells (red) and some alveolar macrophages (data not shown) of SootH-exposed mice. No staining was detected in sham- or SootL-exposed lungs. Agglomerates from SootH and SootL particles are clearly visible in the lungs. The arrow indicates a SootH-loaded macrophage containing agglomerated particles.

Figure 5

Mechanistic model for particle-related proinflammatory response that is consistent with our in vivo and in vitro data for CDNPs. The inflammatory signaling cascade is activated by oxidative stress due to the combined effects of the particles’ innate surface reactivity (measured as Ox_Pot; pathway 1) and the presence of bioavailable organic compounds (Cyp1a1 induction; pathway 2), which are eliminated via a three-phase detoxification process. Abbreviations: H, high; L, low; PM, particulate matter.

Figure 6

The predictive capacity of two simple linear models for the measured I_Ef. Although the one-parameter regression model based on Ox_Pot only (I_Ef = 5.14Ox_Pot) represents 77% of the observed variability in I_Ef, the two-parameter model (Ox_Pot and Cyp1a1 induction; see Equation 2), which considers the combined effects of pathway 1 and pathway 2, explains about 94%.