Screening for oxidative damage by engineered nanomaterials: a comparative evaluation of FRAS and DCFH View Full Text


Ontology type: schema:ScholarlyArticle     


Article Info

DATE

2014-02

AUTHORS

Anoop K. Pal, Shu-Feng Hsieh, Madhu Khatri, Jacqueline A. Isaacs, Philip Demokritou, Peter Gaines, Daniel F. Schmidt, Eugene J. Rogers, Dhimiter Bello

ABSTRACT

Several acellular assays are routinely used to measure oxidative stress elicited by engineered nanomaterials (ENMs), yet little comparative evaluations of such methods exist. This study compares for the first time the performance of the dichlorofluorescein (DCFH) assay which measures reactive oxygen species (ROS) generation, to that of the ferric-reducing ability of serum (FRAS) assay, which measures biological oxidant damage in serum. A diverse set of 28 commercially important and extensively characterized ENMs were tested on both the assays. Intracellular oxidative stress was also assessed on a representative subset of seven ENMs in THP-1 (phorbol 12-myristate 13-acetate matured human monocytes) cells. Associations between assay responses and ENM physicochemical properties were assessed via correlation and regression analysis. DCFH correlated strongly with FRAS after dose normalization for mass (R2 = 0.78) and surface area (R2 = 0.68). Only 10/28 ENMs were positive in DCFH versus 21/28 in FRAS. Both assays were strongly associated with specific surface area and transition metal content. Qualitatively, a similar response ranking was observed for acellular FRAS and intracellular reduced:oxidized glutathione ratio (GSH:GSSG) in cells. Quantitatively, weak correlation was found between intracellular GSSG and FRAS or DCFH (R2 < 0.25) even after calculating effective dose to cells. The FRAS assay was more sensitive than DCFH, especially for ENMs with low to moderate oxidative damage potential, and may serve as a more biologically relevant substitute for acellular ROS measurements of ENMs. Further in vitro and in vivo validations of FRAS against other toxicological endpoints with larger datasets are recommended. More... »

PAGES

2167

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/s11051-013-2167-3

DOI

http://dx.doi.org/10.1007/s11051-013-2167-3

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1006118717


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